JP4329453B2 - Image signal processing apparatus and method, recording medium, and program - Google Patents

Description

The present invention relates to an image signal processing apparatus and method , a recording medium, and a program, and more particularly, to an image signal processing apparatus and method , a recording medium, and a program that make it possible to fully utilize the viewing characteristics of individual users. .

  As an image signal processing apparatus that performs processing for converting a first image signal into a second image signal, for example, an NTSC (National Television System Committee) mounted on a television receiver (hereinafter simply referred to as a television) or the like. A method of converting a video signal of a system into a high-definition video signal has been proposed (see, for example, Patent Documents 1, 2, and 3). As one type of image signal processing apparatus, a noise removal apparatus that can be applied to a television or the like and that removes noise included in an image signal has also been proposed (see, for example, Patent Document 4).

  By the way, the television is provided to the user with a remote commander (hereinafter referred to as a remote controller) that transmits an operation command corresponding to the user's operation such as channel selection to the television main body by radio communication such as radio waves. Is common.

  Recently, there is a remote controller that can operate not only a television but also a device other than a television such as a VTR (Video Tape Recorder) connected to the television.

  When the user operates the remote controller, for example, operation commands such as selection of a television channel, reproduction of a VTR (Video Tape Recorder), and fast-forwarding are transmitted to the television body and the VTR. The TV main body and the VTR receive an operation command from the remote controller and perform control corresponding to the received operation command.

JP 10-313445 A Japanese Patent Laid-Open No. 11-355731 JP 2002-196737 A JP 2000-59652 A

  However, it has not been done so far to change a predetermined process in the television, for example, a process for converting the image quality to a high image quality, in response to an operation command transmitted from the remote controller. For example, the operation command transmitted from the remote control can recognize the channel displayed on the screen by the television, but the content of the process for converting the image quality is not changed for each channel.

  In addition, in the operation commands transmitted from the remote controller, such as selection of TV channels, VTR playback, fast forward, and the like, if the contents (data) operated by the user are aggregated, the individual user (or household) ) Shows the characteristics of TV viewing.

  For example, if the data of the channel selected by the user is aggregated, the user's favorite channel can be estimated. In addition, for example, by collecting operation data such as VTR playback, fast forward, and slow playback, it is possible to estimate the operation characteristics (癖) of the user in VTR playback.

  However, in conventional devices such as televisions, the operation commands operated by the remote controller are simply transmitted to the device and used only for controlling the device, and are used as data for estimating the personal viewing characteristics of the user. It never happened. Therefore, it cannot be said that conventional devices such as televisions perform processing that fully utilizes the user's individual viewing characteristics.

  The present invention has been made in view of such a situation, and makes it possible to fully utilize the viewing characteristics of individual users.

An image signal processing apparatus of the present invention includes a first command receiving unit that receives an operation command from the outside, an execution unit that executes a process according to the operation command received by the first command receiving unit, and an image signal Image signal processing means for processing the image signal and utilization means used for processing in the image signal processing means. The utilization means is constituted by a semiconductor chip and is detachable from the image signal processing apparatus. Based on the second command receiving means that receives the same operation command as the operation command received by the command receiving means, and the operation command received by the second command receiving means, the processing in the image signal processing means is controlled. And at least control means.

Image signal processing method of the present invention includes an executing step of executing the first command receiving step of receiving the operation command from the outside, the processing corresponding to the operation command received by the processing of the first command receiving step, An image signal processing step for processing the image signal, a second command receiving step for causing the utilization means to receive the same operation command as the operation command received in the first command receiving step, and a second command receiving step. And a control step for controlling the processing in the image signal processing step based on the operation command received in the processing.

A program of a recording medium of the present invention includes an executing step of executing the first command receiving step of receiving the operation command from the outside, the processing corresponding to the operation command received by the processing of the first command receiving step, An image signal processing step for processing the image signal, a second command receiving step for causing the utilization means to receive the same operation command as the operation command received in the first command receiving step, and a second command receiving step. And a control step for controlling the processing in the image signal processing step based on the operation command received in the processing.

Program of the present invention includes a first command receiving step of receiving the operation command from the outside, and execution step executes processing corresponding to the operation command received by the processing of the first command receiving step, an image signal An image signal processing step to be processed, a second command reception step for causing the utilization means to receive the same operation command as the operation command received in the first command reception step, and reception in the processing of the second command reception step The computer is caused to execute a control step for controlling processing in the image signal processing step based on the operated command.

In the image signal processing apparatus and method, the recording medium, and the program of the present invention, an external operation command is received, processing according to the received operation command is executed, and the image signal is processed. Further, in the utilization means used for image signal processing for processing the image signal, the same operation command is received, and the image signal processing is controlled based on the received operation command.

The image signal device may be an independent device or a block that performs image signal processing of one device.

  According to the present invention, it is possible to fully utilize the viewing characteristics of individual users.

  Embodiments of the present invention will be described below. Correspondences between constituent elements described in the claims and specific examples in the embodiments of the present invention are exemplified as follows. This description is to confirm that specific examples supporting the invention described in the claims are described in the embodiments of the invention. Therefore, even if there are specific examples that are described in the embodiment of the invention but are not described here as corresponding to the configuration requirements, the specific examples are not included in the configuration. It does not mean that it does not correspond to a requirement. On the contrary, even if a specific example is described here as corresponding to a configuration requirement, this means that the specific example does not correspond to a configuration requirement other than the configuration requirement. not.

  Further, this description does not mean that all the inventions corresponding to the specific examples described in the embodiments of the invention are described in the claims. In other words, this description is an invention corresponding to the specific example described in the embodiment of the invention, and the existence of an invention not described in the claims of this application, that is, in the future, a divisional application will be made. Nor does it deny the existence of an invention added by amendment.

An image signal processing apparatus according to claim 1 is provided.
In an image signal processing apparatus (for example, the television receiver 1 in FIG. 2) that processes an image signal,
A first command receiving means for receiving an operation command from the outside (for example, the remote control radio wave receiving circuit 17 in FIG. 2);
Execution means (for example, the control circuit 18 in FIG. 2) for executing processing according to the operation command received by the first command receiving means;
Image signal processing means for processing the image signal (for example, the image signal processing circuit 14 in FIG. 2);
Use means (for example, bay 3 in FIG. 2) used for processing in the image signal processing means,
The utilization means is composed of a semiconductor chip and is detachable from the image signal processing device.
Second command receiving means (for example, remote control radio wave receiving circuit 73 in FIG. 8) for receiving the same operation command as the operation command received by the first command receiving means;
And at least control means (for example, a selection switch 72 in FIG. 8) for controlling processing in the image signal processing means based on the operation command received by the second command receiving means.

An image signal processing apparatus according to claim 3 is provided.
The control means is a prediction coefficient storage means (for example, a prediction coefficient storage means for storing a prediction coefficient for each predetermined class obtained in advance by learning, which is used to convert the first image signal into the second image signal. A storage unit 71) of FIG.
The image signal processing means includes
Class classification means (for example, the class classification unit 32 in FIG. 3) for performing class classification for classifying the second image signal into any one of a plurality of classes;
Calculation means for obtaining the second image signal by calculation using the prediction coefficient of the class of the second image signal and the first image signal (for example, the prediction calculation circuit 35 in FIG. 3); It is characterized by having.

An image signal processing apparatus according to claim 5 is provided.
A television signal receiving means for receiving a television signal (for example, the antenna 12 of FIG. 2);
Channel selection means (for example, the tuner 13 in FIG. 2) for selecting an image signal of a predetermined channel from the television signal;
The execution means executes processing for causing the channel selection means to select an image signal of a predetermined channel based on the operation command received by the first command reception means,
The image signal processing means obtains the second image signal by using the image signal selected by the channel selection means as the first image signal.

An image signal processing device according to claim 6 is provided.
The utilization means is:
Based on the operation command received by the second command receiving means, channel selection frequency counting means for counting the channel selection frequency at which the channel of the television signal is selected (for example, the channel frequency counting circuit 125 of FIG. 14). )When,
It further has channel selection frequency storage means (for example, memory 126 in FIG. 14) for storing the channel selection frequency.

An image signal processing apparatus according to claim 9 is provided.
The utilization means is:
Reproduction speed selection frequency counting means (for example, reproduction speed frequency counting circuit 205 in FIG. 22) that counts the reproduction speed selection frequency at which the reproduction speed is selected based on the operation command received by the second command receiving means. )When,
Reproduction speed selection frequency storage means (for example, the memory 206 in FIG. 22) for storing the reproduction speed selection frequency is further included.

An image signal processing apparatus according to claim 11 is provided.
The utilization means is:
Reproduction device selection frequency counting means for counting the reproduction device selection frequency selected by the reproduction device based on the operation command received by the second command reception means (for example, the image source selection frequency counting circuit of FIG. 31). 275) and
Reproducing apparatus selection frequency storage means (for example, the memory 276 in FIG. 31) for storing the reproducing apparatus selection frequency is further provided.

An image signal processing apparatus according to claim 12 is provided.
The prediction coefficient storage means stores a plurality of sets of prediction coefficients obtained by learning using different types of images,
The image signal processing means converts an image signal reproduced in a recording / reproducing apparatus that records and reproduces an image signal into the second image signal as the first image signal,
The control means discriminates the recording / reproducing apparatus reproducing an image signal based on the operation command received by the second command receiving means, and the prediction coefficient storage means according to the discrimination result Control the processing in the image signal processing means by selecting any one of the plurality of sets of prediction coefficients stored in and supplying the prediction coefficient to the computing means,
Learning means for learning a new prediction coefficient using the image signal before being recorded in the recording / reproducing apparatus and the image signal recorded and reproduced in the recording / reproducing apparatus (for example, the learning circuit 303 in FIG. 35). )When,
Update means for updating the storage contents of the prediction coefficient storage means with the new prediction coefficient (for example, step S116 of FIG. 37 performed by the learning circuit of FIG. 35).

An image signal processing apparatus according to claim 13 is provided.
Resizing means for resizing the image signal and outputting the resized image signal (for example, resizing circuit 143 in FIG. 17) is further provided.
The execution unit executes a process of setting a resizing rate when the image is resized by the resizing unit based on the operation command received by the first command receiving unit.
The image signal processing means obtains the second image signal by using the resized image signal as the first image signal.

The image signal processing method according to claim 14 comprises:
An image signal processing apparatus comprising utilization means used for image signal processing for processing an image signal , wherein the utilization means is constituted by a semiconductor chip and is detachable from the image signal processing apparatus In the image signal processing method of the processing device ,
A first command receiving step for receiving an operation command from the outside (for example, processing performed by the remote control radio wave receiving circuit 17 in FIG. 2);
An execution step (for example, a process performed by the control circuit 18 in FIG. 2) for executing a process according to the operation command received in the process of the first command receiving step;
An image signal processing step (for example, step S25 in FIG. 10) for processing the image signal;
In the utilization means,
A second command receiving step (for example, step S41 in FIG. 11) for receiving the same operation command as the operation command received in the first command receiving step;
And a control step (for example, step S44 in FIG. 11) for controlling processing in the image signal processing step based on the operation command received in the processing in the second command receiving step.

The recording medium program according to claim 15 and the specific example of each step of the program according to claim 16 are the same as the specific example in the embodiment of the invention of each step of the image signal processing method according to claim 14. It is.

(First embodiment)
FIG. 1 is a perspective view showing an embodiment of a television receiver 1 to which the present invention is applied.

  In FIG. 1, a television receiver 1 (hereinafter referred to as a television 1) displays an image signal input to the television 1 on a screen. Here, the image signal input to the television 1 includes an image signal input from an external device via an input terminal or the like in addition to an image signal received by the television 1 itself. A small concave slot 2 is formed in the lower right of the front, which is the same surface as the (display) screen of the television 1, so that a small electronic device 3 (hereinafter referred to as a bay 3) can be mounted. ing. In FIG. 1, only one slot 2 is provided in the television 1, but the television 1 can be provided with a plurality of slots and a plurality of bays can be mounted.

  The user operates the remote commander 4 (hereinafter referred to as the remote controller 4), for example, when selecting a channel of a program to be viewed. The remote controller 4 transmits an operation command corresponding to the user's operation to the television 1 by radio such as radio waves.

  The operation command transmitted from the remote controller 4 by radio is received by the remote control receiver 5 arranged on the left side of the slot 2 and further received by the bay 3 attached to the slot 2 of the television 1. Then, based on the operation command received by the remote control receiver 5, the television 1 displays the input image signal on the screen.

  Here, the bay 3 is composed of, for example, an IC (Integrated Circuit) chip or the like, and is detachable from the television 1 (slot 2 thereof). The circuit in the bay 3 is used for image signal processing of the television 1. For example, the circuit in the bay 3 performs an image conversion process of converting a first image signal as an image signal having a predetermined resolution into a second image signal as an image signal having a resolution higher than the resolution of the image signal. Do.

  Further, as described above, the bay 3 can be attached to and detached from the television 1, and the bay 3 is upgraded by replacing the bay 3 with a new bay 3 in which software (program or data) in the bay 3 is changed. It becomes possible to do. Here, the version upgrade of the bay 3 can also be performed by changing a circuit (hardware) in the bay 3.

  For example, in the bay 3 initially installed in the TV 1 (slot 2), the image signal input to the TV 1 is a 525i signal (D1 output) with 525 scanning lines and an interlaced scanning method. ). Then, the signal after being converted into the 525i signal is displayed on the screen of the television 1.

  Then, by upgrading the bay 3, the bay 3 has, for example, 525 scanning lines in addition to (or instead of) the image signal processing for converting the image signal input to the television 1 into a 525i signal. Thus, the scanning method can be converted into a 525p signal (D2 output) which is a progressive method.

  Further, by upgrading the bay 3, for example, it is possible to add a function corresponding to a zoom that improves the image quality of a zoomed image signal input to the TV 1, or it is played back in slow motion, and the TV It is also possible to add a function corresponding to slow motion for improving the image quality of the image signal input to 1.

  Such upgrade of the bay 3 is often performed together with the upgrade of the remote controller 4 because the remote controller 4 needs to have an operation command corresponding to the function added by the upgrade. For example, when the bay 3 is upgraded to a version to which a zoom function is added, the remote controller 4 is also upgraded so that the user can select (instruct) the zoom function on the remote controller 4.

  As a method for upgrading the bay 3 and the remote control 4, for example, a set of the upgraded bay 3 and the remote control 4 is sold, and the user purchases the set and replaces the bay 3 and the remote control 4. is there. However, with this method, the user must go to the store that sells the bay 3 and the remote control 4 to see if they are upgraded, and the user feels bothersome. It is not preferable.

  Therefore, for example, the maker 3 (for example, the manufacturer or distributor of the television 1) announces that the bay 3 and the remote controller 4 have been upgraded, and the user is now attached to the television 1 at that time. There is a method for upgrading the set of the bay 3 and the remote control 4 by sending the set of the bay 3 and the remote control 4 to the apparatus manufacturer and having the upgraded bay 3 and the remote control 4 returned.

  In the present embodiment, the upgrade of the bay 3 and the remote control 4 is performed by the apparatus manufacturer temporarily collecting a set of the bay 3 and the remote control 4 owned by the user and replacing the set with the upgraded bay 3 and the remote control 4. It shall be done by

  FIG. 2 is a block diagram showing a configuration example of the first embodiment of the television 1 of FIG.

  The television 1 (main body) includes a tuner 13 that constitutes an image signal input unit 11, an image signal processing circuit 14, a CRT (Cathode Ray Tube) 16, a remote control radio wave reception circuit 17 that constitutes a remote control reception unit 5, and a control circuit 18. Composed.

  The antenna 12 receives a television signal (radio wave) sent from a broadcasting station and supplies it to the tuner 13. The antenna 12 can receive television signals such as terrestrial, BS (Broadcasting Satellite), and CS (Communications Satellite). Here, the television signal sent from the broadcasting station includes a so-called color bar image that is used as a test image (test signal) periodically or at irregular predetermined times. .

  The tuner 13 selects the television signal of the channel selected by the user by operating the remote controller 4 based on the control of the control circuit 18 from the television signals supplied from the antenna 12. Further, the tuner 13 supplies the selected television signal to the image signal processing circuit 14. Here, the television signal supplied to the image signal processing circuit 14 includes, for example, an audio signal and an image signal. In the present embodiment, the image signal processing circuit 14 Processing shall be performed. Therefore, the following description will be made with attention paid to an image signal (hereinafter referred to as an input image signal) in a television signal. Note that the same processing as described below can be performed on the audio signal.

  The image signal processing circuit 14 performs various types of image signal processing while exchanging data with the coefficient generation circuit 15 in the bay 3. One of the image signal processes performed by the image signal processing circuit 14 is an image conversion process for converting an image signal from a first image signal to a second image signal.

  Here, for example, if the first image signal is a low resolution image signal and the second image signal is a high resolution image signal, the image conversion process is a resolution improvement process for improving the resolution. it can. Further, for example, if the first image signal is a low S / N (Signal / Noise) image signal and the second image signal is a high S / N image signal, the image conversion process may reduce noise. It can be referred to as noise removal processing for removal.

  Therefore, according to the image conversion process, various processes can be realized depending on how the first and second image signals are defined.

  In the first embodiment, the image signal processing circuit 14 performs an image conversion process for converting the image signal supplied from the tuner 13 into a high-quality image signal.

  The image signal processing circuit 14 outputs a class code corresponding to a class obtained by performing class classification, which will be described later, and an image signal supplied from the tuner 13 to the coefficient generation circuit 15. The coefficient generation circuit 15 obtains a tap coefficient described later from the class code supplied from the image signal processing circuit 14 and supplies the tap coefficient to the image signal processing circuit 14. Then, the image signal processing circuit 14 generates a high quality image using the tap coefficient supplied from the coefficient generation circuit 15 and supplies it to the CRT 16. The detailed configurations of the image signal processing circuit 14 and the coefficient generation circuit 15 will be described later with reference to FIG.

  The CRT 16 displays a high-quality image signal supplied from the image signal processing circuit 14 on the screen. The CRT 16 may be another display such as an LCD (Liquid Crystal Display).

  The remote control radio wave reception circuit 17 receives an operation command corresponding to a user operation transmitted from the remote control 4. Further, the remote control radio wave receiving circuit 17 supplies the received operation command to the control circuit 18.

  The control circuit 18 controls each part of the television 1 according to the operation command supplied from the remote control radio wave reception circuit 17 (executes processing according to the operation command). For example, when the user operates the remote controller 4 to select any channel of terrestrial, BS, or CS, the control circuit 18 causes the tuner 13 to select an image signal of the channel corresponding to the selection. To control.

  In the television 1 configured as described above, the image signal of the channel selected by the user operating the remote controller 4 from the image signals received by the antenna 12 is displayed in the image signal processing circuit 14 as a high-quality image. And is displayed on the CRT 16.

  FIG. 3 is a block diagram showing a detailed configuration of the image signal processing circuit 14 of FIG.

  The image signal processing circuit 14 converts an image signal supplied from the tuner 13 as a first image signal, and converts the first image signal into a high-quality image signal as a second image signal.

  That is, in the image signal processing circuit 14, the image signal supplied from the tuner 13 is generated as a first image signal by the prediction tap extraction circuit 31, the class tap extraction circuit 33 of the class classification unit 32, and the coefficient generation in the bay 3. It is supplied to the circuit 15.

  The prediction tap extraction circuit 31 sequentially sets a pixel constituting the second image signal as a pixel of interest, and further, a pixel (pixel of the pixel constituting the first image signal used for predicting the pixel value of the pixel of interest. Some of the values are extracted as prediction taps.

  Specifically, the prediction tap extraction circuit 31 includes a pixel of the first image signal corresponding to the target pixel (for example, a pixel of the first image signal that is closest to the target pixel spatially and temporally). ), A plurality of pixels at spatially or temporally close positions are extracted as prediction taps from the first image signal.

  The prediction tap extraction circuit 31 supplies the extracted prediction tap to the prediction calculation circuit 35.

  The class classification unit 32 includes a class tap extraction circuit 33 and a class code generation circuit 34, and classifies the target pixel according to the shape of the level distribution of the image signal supplied from the tuner 13. That is, the class tap extraction circuit 33 obtains a class tap from the image signal supplied by the tuner 13, and the class code generation circuit 34 obtains a class code from the class tap.

  That is, the class tap extraction circuit 33 classifies some of the pixels constituting the first image signal used for classifying the target pixel into any one of several classes. Extract as a tap.

  Note that the prediction tap and the class tap may have the same tap structure or different tap structures.

  The class tap obtained by the class tap extraction circuit 33 is supplied to the class code generation circuit 34.

  Based on the level distribution of the pixels constituting the class tap from the class tap extraction circuit 33, the class code generation circuit 34 performs class classification for classifying the pixel of interest into one of a plurality of classes. A class code corresponding to the obtained class is generated and supplied to the coefficient generation circuit 15.

  Here, as a method of classifying, for example, ADRC (Adaptive Dynamic Range Coding) or the like can be employed.

  In the method using ADRC, the pixel values of the pixels constituting the class tap are subjected to ADRC processing, and the class of the target pixel is determined according to the ADRC code obtained as a result.

In the K-bit ADRC, for example, the maximum value MAX and the minimum value MIN of the pixel values constituting the class tap are detected, and DR = MAX−MIN is set as the local dynamic range of the set, and this dynamic range Based on DR, the pixel values constituting the class tap are requantized to K bits. That is, the pixel value of each pixel forming the class taps, the minimum value MIN is subtracted, and the subtracted value is divided (quantized) by DR / 2 ^K. A bit string obtained by arranging the pixel values of the K-bit pixels constituting the class tap in a predetermined order is output as an ADRC code. Therefore, for example, when the class tap is subjected to 1-bit ADRC processing, the pixel value of each pixel constituting the class tap is divided by the average value of the maximum value MAX and the minimum value MIN (rounded down). Thereby, the pixel value of each pixel is set to 1 bit (binarized). Then, a bit string in which the 1-bit pixel values are arranged in a predetermined order is output as an ADRC code. For example, the class code generation circuit 34 generates (outputs) an ADRC code obtained by performing ADRC processing on a class tap as a class code.

Note that the class code generation circuit 34 can also output, for example, the level distribution pattern of the pixel values of the pixels constituting the class tap as it is as the class code. However, in this case, if the class tap is composed of pixel values of N pixels and K bits are assigned to the pixel values of each pixel, the class code output by the class code generation circuit 34 The number is (2 ^N ) ^K , which is a huge number that is exponentially proportional to the number of bits K of the pixel value of the pixel.

  Therefore, the class code generation circuit 34 preferably performs class classification by compressing the information amount of the class tap by the above-mentioned ADRC processing or vector quantization.

  The coefficient generation circuit 15 in the bay 3 stores the tap coefficient for each class obtained by learning to be described later, and further corresponds to the class code supplied from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address to be stored (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction calculation circuit 35.

  Here, the tap coefficient corresponds to a coefficient that is multiplied with input data in a so-called tap in the digital filter.

  The coefficient generation circuit 15 calculates the intensity of noise of the image signal input from the tuner 13 from the image signal input from the tuner 13 and the image signal stored in the coefficient generation circuit 15.

  The prediction calculation circuit 35 acquires the prediction tap output from the prediction tap extraction circuit 31 and the tap coefficient output from the coefficient generation circuit 15, and uses the prediction tap and the tap coefficient to predict the true value of the target pixel. A predetermined prediction calculation for obtaining a value is performed. As a result, the prediction calculation circuit 35 obtains and outputs the pixel value of the pixel of interest (predicted value thereof), that is, the pixel value of the pixels constituting the second image signal.

  FIG. 4 shows an example of a tap structure of prediction taps and class taps.

  The left side of FIG. 4 shows an example of the tap structure of the class tap. In FIG. 4, a class tap is configured by nine pixels P1 to P9. That is, in FIG. 4, among the image signals output from the tuner 13, the pixel P5 corresponding to the target pixel, the upward direction (P1, P2), the downward direction (P8, P9), and the left direction (P3, P3) of the pixel. A so-called cross-shaped class tap is constituted by two pixels adjacent to each other in the right direction (P6, P7).

  The right side of FIG. 4 shows an example of the tap structure of the prediction tap. In FIG. 4, a prediction tap is composed of 13 pixels. That is, in FIG. 4, among the image signals output from the tuner 13, the five pixels arranged in the vertical direction centering on the pixel corresponding to the target pixel and the pixels adjacent to the left and right of the pixel corresponding to the target pixel are centered. In other words, each of the three pixels arranged in the vertical direction and the pixels that are separated from the pixel corresponding to the target pixel by one pixel to the left and right constitute a diamond-shaped class tap.

  Next, prediction calculation in the prediction calculation circuit 35 of FIG. 3 and learning of tap coefficients used for the prediction calculation will be described.

  Now, the high-quality image signal (high-quality image signal) is used as the second image signal, and the high-quality image signal is filtered by LPF (Low Pass Filter) to reduce the image quality (resolution). Using a low-quality image signal (low-quality image signal) as a first image signal, a prediction tap is extracted from the low-quality image signal, and the pixel value of the high-quality pixel is set to a predetermined value using the prediction tap and the tap coefficient. Consider obtaining (predicting) by prediction calculation.

  Assuming that, for example, linear primary prediction calculation is adopted as the predetermined prediction calculation, the pixel value y of the high-quality pixel is obtained by the following linear linear expression.

・・・（１）

... (1)

In Equation (1), x _n represents the pixel value of the pixel of the n-th low-quality image signal (hereinafter referred to as “low-quality pixel” as appropriate) that constitutes the prediction tap for the high-quality pixel y, and w _n represents the nth tap coefficient multiplied by the nth low image quality pixel (its pixel value). In equation (1), the prediction tap is assumed to be composed of N low image quality pixels x ₁ , x ₂ ,..., X _N.

  Here, the pixel value y of the high-quality pixel can be obtained not by the linear primary expression shown in Expression (1) but by a higher-order expression of the second or higher order.

Now, when the true value of the pixel value of the high-quality pixel of the k-th sample is expressed as y _k and the predicted value of the true value y _k obtained by the equation (1) is expressed as y _k ′, the prediction error e _k Is expressed by the following equation.

・・・（２）

... (2)

Now, since the predicted value y _k ′ of Equation (2) is obtained according to Equation (1), the following equation is obtained by replacing y _k ′ of Equation (2) according to Equation (1).

・・・（３）

... (3)

In Equation (3), x _{n, k} represents the nth low-quality pixel that constitutes the prediction tap for the high-quality pixel of the k-th sample.

Tap coefficient w _n for the prediction error e _k 0 of the formula (3) (or Equation (2)) is, is the optimal for predicting the high-quality pixel, for all the high-quality pixel, such In general, it is difficult to obtain a large tap coefficient w _n .

Therefore, as the standard for indicating that the tap coefficient w _n is optimal, for example, when adopting the method of least squares, optimal tap coefficient w _n, the sum E of square errors expressed by the following formula It can be obtained by minimizing.

・・・（４）

... (4)

However, in Equation (4), K is the high image quality pixel y _k and the low image quality pixels x _{1, k} , x _{2, k} ,..., X _N constituting the prediction tap for the high image quality pixel y _{k. , k} represents the number of samples (the number of learning samples).

The minimum value of the sum E of square errors of Equation (4) (minimum value), as shown in equation (14) is given a material obtained by partially differentiating the sum E with the tap coefficient w _n by w _n to 0.

・・・（５）

... (5)

Therefore, when partial differentiation of above equation (3) with the tap coefficient w _n, the following equation is obtained.

・・・（６）

... (6)

  From the equations (5) and (6), the following equation is obtained.

・・・（７）

... (7)

By substituting equation (3) into e _k in equation (7), equation (7) can be expressed by the normal equation shown in equation (8).

・・・（８）

... (8)

Normal equation of Equation (8), for example, by using a like sweeping-out method (Gauss-Jordan elimination method) can be solved for the tap coefficient w _n.

By solving the normal equations in equation (8) for each class, the optimal tap coefficient (here, the tap coefficient that minimizes the sum E of square errors) to w _n, can be found for each class.

Figure 5 shows an example of the configuration of a learning apparatus that performs learning for determining the tap coefficient w _n for each class by solving the normal equations in equation (8).

The learning device, so that the learning image signal used for learning of the tap coefficient w _n is input. Here, as the learning image signal, for example, a high-resolution image signal with high resolution can be used.

  In the learning apparatus, the learning image signal is supplied to the teacher data generation unit 51 and the student data generation unit 53.

  The teacher data generation unit 51 generates teacher data serving as a learning teacher (answer) from the learning image signal supplied thereto, and supplies it to the teacher data storage unit 52. That is, here, the teacher data generation unit 51 supplies the high-quality image signal as the learning image signal as it is to the teacher data storage unit 52 as teacher data.

  The teacher data storage unit 52 stores a high-quality image signal as teacher data supplied from the teacher data generation unit 51.

  The student data generation unit 53 generates student data to be a learning student from the learning image signal and supplies it to the student data storage unit 54. In other words, the student data generation unit 53 generates a low-quality image signal by filtering the high-quality image signal as the learning image signal, thereby reducing the resolution. To the student data storage unit 54.

  The student data storage unit 54 stores the student data supplied from the student data generation unit 53.

  The prediction tap extraction unit 55 sequentially sets pixels constituting the high-quality image signal as the teacher data stored in the teacher data storage unit 52 as the attention teacher pixels, and stores the attention teacher pixels in the student data storage unit 54. The prediction tap having the same tap structure as that formed by the prediction tap extraction circuit 31 of FIG. 3 is configured by extracting predetermined ones of the low-quality pixels constituting the low-quality image signal as the student data. And supplied to the add-in portion 58.

  The class tap extraction unit 56 extracts a predetermined one of the low-quality pixels constituting the low-quality image signal as the student data stored in the student data storage unit 54 for the teacher pixel of interest, as shown in FIG. A class tap having the same tap structure as that formed by the class tap extraction circuit 33 is configured and supplied to the class code generation unit 57.

  The class code generation unit 57 performs the same class classification as the class code generation circuit 34 of FIG. 3 based on the class tap output from the class tap extraction unit 56, and adds the class code corresponding to the resulting class. To the unit 58.

  The adding unit 58 reads the attention teacher pixel from the teacher data storage unit 52, and obtains the attention teacher pixel and the student data constituting the prediction tap configured for the attention teacher pixel supplied from the prediction tap extraction unit 55. The target addition is performed for each class code supplied from the class code generator 57.

That is, the adder 58 is supplied with the teacher data y _k stored in the teacher data storage 52, the prediction tap x _{n, k} output from the prediction tap extractor 55, and the class code output from the class code generator 57. Is done.

Then, the adding unit 58 uses the prediction tap (student data) x _{n, k} for each class corresponding to the class code supplied from the class code generating unit 57 _, and uses the student data in the matrix on the left side of Equation (8). An operation corresponding to multiplication (x _{n, k} x _{n ′, k} ) and summation (Σ) is performed.

Further, the adding unit 58 again uses the prediction tap (student data) x _{n, k} and the teacher data y _k for each class corresponding to the class code supplied from the class code generating unit 57, and the equation (8). Is multiplied by the student data x _{n, k} and the teacher data y _k (x _{n, k} y _k ) in the vector on the right side of _, and an operation corresponding to summation (Σ) is performed.

That is, the adding unit 58 performs the left-side matrix component (Σx _{n, k} x _{n ′, k} ) and the right-side vector component in Equation (8) previously obtained for the teacher data set as the focused teacher pixel. (Σx _{n, k} y _k ) is stored in its built-in memory (not shown), and the matrix component (Σx _{n, k} x _{n ′, k} ) or vector component (Σx _{n, k} y) _k ), the corresponding component x _{n, k + 1} calculated using the teacher data y _{k + 1} and the student data x _{n, k + 1} for the teacher data newly selected as the teacher pixel of interest. x _{n ′, k + 1} or x _{n, k + 1} y _{k + 1} is added (addition represented by the summation of Expression (8) is performed).

  Then, the addition unit 58 performs the above-described addition using all the teacher data stored in the teacher data storage unit 52 as the target teacher pixel, thereby obtaining the normal equation shown in Expression (8) for each class. Then, the normal equation is supplied to the tap coefficient calculation unit 59.

Tap coefficient calculating section 59 solves the normal equations for each class supplied from the adder 58, for each class, and outputs the determined optimal tap coefficient w _n.

In the coefficient generation circuit 15 in the bay 3 of FIG. 3, for example, the tap coefficient w _m for each class obtained as described above is stored.

  In the above-described case, the learning image signal is used as teacher data corresponding to the second image signal as it is, and the low-quality image signal obtained by degrading the resolution of the learning image signal is used as the first image. Since the tap coefficient is learned as the student data corresponding to the signal, the tap coefficient is a resolution improvement process for converting the first image signal into the second image signal whose resolution is improved. What performs the image conversion process of this can be obtained.

  Here, depending on the selection method of the student data corresponding to the first image signal and the image signal to be the teacher data corresponding to the second image signal, tap coefficients that perform various image conversion processes are obtained. be able to.

  That is, for example, a high-quality image signal is used as teacher data, and a learning process is performed on the high-quality image signal as the teacher data by using an image signal on which noise is superimposed as student data. Thus, it is possible to obtain an image conversion process as a noise removal process for converting the first image signal into a second image signal from which noise contained therein is removed (reduced).

  Next, processing (learning processing) of the learning device in FIG. 5 will be described with reference to the flowchart in FIG.

  First, in step S1, the teacher data generation unit 51 and the student data generation unit 53 respectively generate and output teacher data and student data from the learning image signal. That is, the teacher data generation unit 51 outputs the learning image signal as it is as teacher data. The student data generation unit 31 generates student data for the teacher data (learning image signal) of each frame (or field) by filtering the learning image signal with an LPF having a predetermined cutoff frequency. Output.

  The teacher data output from the teacher data generation unit 51 is supplied to and stored in the teacher data storage unit 52, and the student data output from the student data generation unit 53 is supplied to and stored in the student data storage unit.

  After that, the process proceeds to step S <b> 2, and the prediction tap extraction unit 55 sets the teacher data stored in the teacher data storage unit 52 as notable teacher pixels that have not yet been identified as the notable teacher pixels. Further, in step S 2, the prediction tap extraction unit 55 configures a prediction tap from the student data stored in the student data storage unit 54 for the teacher pixel of interest and supplies the prediction tap to the addition unit 58, and the class tap extraction unit 56. However, for the teacher pixel of interest, a class tap is constructed from the student data stored in the student data storage unit 54 and supplied to the class code generation unit 57.

  Then, the process proceeds to step S 3, where the class code generation unit 57 classifies the target teacher pixel based on the class tap for the target teacher pixel, and adds the class code corresponding to the resulting class to the addition unit 58. Output, and go to step S4.

  In step S <b> 4, the adding unit 58 reads the target teacher pixel from the teacher data storage unit 52 and configures the prediction tap configured for the target teacher pixel and the target teacher pixel supplied from the prediction tap extraction unit 55. The addition of Expression (8) for the student data is performed for each class code supplied from the class code generation unit 57, and the process proceeds to Step S5.

  In step S <b> 5, the prediction tap extraction unit 55 determines whether or not teacher data that is not yet a teacher pixel of interest is stored in the teacher data storage unit 52. If it is determined in step S5 that the teacher data that is not the attention teacher pixel is still stored in the teacher data storage unit 52, the prediction tap extraction unit 55 newly sets the teacher data that is not yet the attention teacher pixel. Returning to step S2 as the teacher pixel of interest, the same processing is repeated thereafter.

  If it is determined in step S5 that the teacher data that is not the attention teacher pixel is not stored in the teacher data storage unit 52, the adding unit 58 determines the formula ( The matrix on the left side and the vector on the right side in 8) are supplied to the tap coefficient calculation unit 59, and the process proceeds to step S6.

In step S6, the tap coefficient calculation unit 59 solves the normal equation for each class constituted by the matrix on the left side and the vector on the right side in the equation (8) for each class supplied from the adding unit 58, thereby classifying each class. to, and determines and outputs the tap coefficient w _n, the process ends.

  It should be noted that due to the number of learning image signals being insufficient, etc., there may occur a class in which the number of normal equations necessary for obtaining the tap coefficient cannot be obtained. The tap coefficient calculation unit 59 outputs, for example, preset tap coefficients.

  Next, the image conversion processing of the image processing signal circuit 14 and the coefficient generation circuit 15 of FIG. 3 will be described with reference to the flowchart of FIG.

  First, in step S11, the prediction tap extraction circuit 31 sequentially sets pixels constituting the second image signal as the target pixel, and further uses the first image signal used to predict the pixel value of the target pixel. Are extracted as prediction taps. Further, the prediction tap extraction circuit 31 supplies the extracted prediction tap to the prediction calculation circuit 35, and proceeds to step S12.

  In step S12, the class tap extraction circuit 33 selects some of the pixels constituting the first image signal used for classifying the target pixel into any one of several classes. Extract as a class tap. Further, the class tap extraction circuit 33 supplies the obtained class tap to the class code generation circuit 34, and proceeds to step S13.

  In step S13, the class code generation circuit 34 performs class classification for classifying the target pixel into any one of a plurality of classes based on the level distribution of the pixels constituting the class tap from the class tap extraction circuit 33. And generate a class code corresponding to the resulting class. Further, the class code generation circuit 34 supplies the class code to the coefficient generation circuit 15 and proceeds to step S14.

  In step S14, the coefficient generation circuit 15 determines the tap coefficient stored in the address corresponding to the class code supplied from the class code generation circuit 34 (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34). ) Is supplied (output) to the prediction calculation circuit 35.

  And it progresses to step S15, the prediction calculation circuit 35 acquires the prediction tap which the prediction tap extraction circuit 31 outputs, and the tap coefficient which the coefficient generation circuit 15 outputs, and uses the prediction tap and tap coefficient, A predetermined prediction calculation for obtaining a true predicted value of the target pixel is performed. Thereby, the prediction calculation circuit 35 outputs the pixel value of the pixel of interest (predicted value thereof), that is, the pixel value of the pixels constituting the second image signal, and proceeds to step S16.

  In step S16, the image signal processing circuit 14 determines whether or not the input image signal is finished. If it is determined that the input image signal has not ended, the process returns to step S11 and the subsequent processing is repeated.

  On the other hand, if it is determined in step S16 that the input image signal has ended, the process ends.

  As described above, the image signal processing circuit 14 can obtain and output a high-quality image from the input image signal.

  FIG. 8 is a block diagram showing a detailed configuration example of the coefficient generation circuit 15 of FIG.

  The coefficient generation circuit 15 includes a storage unit 71, a selection switch 72, a remote control radio wave reception circuit 73, and a reception noise detection unit 74. The storage unit 71 includes a terrestrial ROM table 81, a BS ROM table 82, a CS ROM table 83, and a default ROM table 84. Further, the reception noise detection unit 74 includes a noise intensity calculation circuit 85, a test signal memory 86, and a noise intensity memory 87.

  The class code output from the class code generation circuit 34 (FIG. 3) is supplied to the ROM tables 81 to 84 of the storage unit 71. The storage unit 71 classifies according to the shape of the level distribution of the input image signal, and stores a table storing tap coefficients (prediction coefficients) obtained by learning in advance for each class for each predetermined type. . In other words, the storage unit 71 stores, for each predetermined type, a table learned using sets of different types of teacher data and student data.

  Radio waves received from the broadcasting station received by the television 1 have different reception conditions depending on the frequency band, and therefore the tap coefficient suitable for the input image signal differs for each frequency band. Also, for each user, if the receiving area is different, the receiving situation is also different, and the tap coefficient suitable for the input image signal may be different for each receiving area.

  Therefore, in the first embodiment, the storage unit 71 stores a table in which tap coefficients are stored for each band (type) of the terrestrial wave, BS, and CS of the input image signal. Here, the table in which the tap coefficients are stored is three types, that is, terrestrial, BS, and CS. However, the band of the input image signal may be further classified, and the types of tables stored in the storage unit 71 Is not limited to the above three types.

  The ROM table 81 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using a terrestrial image signal as an input image signal. In this learning, for example, an image signal of an HD (High Definition) image is used as teacher data, and an SD (Standard Definition) image obtained by down-sampling the HD image and receiving an image signal transmitted by terrestrial waves. Can be used as student data. As a result, it is possible to obtain a tap coefficient capable of removing noise generated by high resolution and propagation on the ground wave. In addition, for example, an image signal of an SD image can be used as teacher data, and an image signal of an SD image obtained by receiving an image signal obtained by transmitting the SD image by terrestrial can be used as student data. Thereby, it is possible to obtain a tap coefficient capable of removing noise generated by propagation on the ground wave.

  The ROM table 82 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using an image signal for BS as an input image signal. The ROM table 83 stores (stores) tap coefficients obtained by learning in advance for each class, which is suitable for performing image conversion processing using an image signal for CS as an input image signal. The teacher data used for learning the tap coefficients stored in the ROM table 82 or 83 can be the same data as the ROM table 81. In addition, the student data used for learning the tap coefficient stored in the ROM table 82 or 83 is the image data sent from the BS or CS instead of the image signal sent by the ground wave in the learning of the ROM table 81. The data can be the same as the ROM table 81 except that it is used.

  The ROM table 84 stores (stores) tap coefficients obtained by learning in advance for each class when the input image signal is an image signal that does not correspond to any of terrestrial, BS, and CS. Here, the value of the tap coefficient for each class stored in the ROM table 84 is, for example, a value that is intermediate between the tap coefficients of the corresponding classes for terrestrial, BS, and CS. Alternatively, by learning all of the teacher data and student data employed in the terrestrial, BS, and CS learning as the teacher data and student data for obtaining the tap coefficients stored in the ROM table 84, respectively, The tap coefficient for each class stored in the ROM table 84 may be obtained.

  Each of the ROM tables 81 to 84 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 72.

  The selection switch 72 selects the output (tap coefficient) of the ROM table of the type associated with the operation command from the outputs of the ROM tables 81 to 84. That is, the selection switch 72 determines the band of the image signal input to the image signal processing circuit 14 based on the operation command supplied from the remote control radio wave receiving circuit 73. Then, the selection switch 72 selects one of the outputs (tap coefficients) of the ROM tables 81 to 84 based on the determined band of the input image signal, and selects the selected tap coefficient from the prediction calculation circuit 35 (FIG. 3). ). Here, since the tap coefficient output from the selection switch 72 is an optimum tap coefficient for the input image signal, it can be said that it is an optimization coefficient.

  The remote control radio wave receiving circuit 73 may supply the selection switch 72 with the band information of the input image signal, that is, information on which of the three types of terrestrial wave, BS, and CS. . In this case, the selection switch 72 does not need to determine the band of the image signal.

  The prediction calculation circuit 35 of FIG. 3 calculates an optimum estimated value by calculation based on the prediction formula of Formula (1) using the tap coefficient that is the output of the ROM table selected by the selection switch 72.

  As described above, the remote control radio wave receiving circuit 73 receives an operation command transmitted wirelessly from the remote control 4. The remote control radio wave reception circuit 73 supplies the received operation command to the selection switch 72 and the noise intensity calculation circuit 85.

  As described with reference to FIG. 2, the television signal transmitted from the broadcast station includes a color bar image at regular or irregular predetermined times. Here, among the image signals input to the image signal processing circuit 14, the image signal of the color bar image is supplied to the noise intensity calculation circuit 85.

  Similarly to the selection switch 72, the noise intensity calculation circuit 85 determines the band of the input image signal based on the operation command supplied from the remote control radio wave reception circuit 73. Further, the noise intensity calculation circuit 85 reads out the image signal of the color bar image corresponding to the determined band of the image signal from the memory 86, and the image signal of the color bar image and the color bar image input from the tuner 13. From the image signal, the noise intensity of the image signal input from the tuner 13 (hereinafter also referred to as noise intensity) is calculated. Further, the noise intensity calculation circuit 85 outputs the calculated noise intensity to the memory 87. Here, the noise intensity calculated by the noise intensity calculation circuit 85 includes a noise amount and the like. In addition, the noise intensity calculation circuit 85 can detect a color shift amount that is a shift in the display position of each display color of the color bar image.

  The memory 86 stores an image signal (test signal) of a high-quality color bar image without noise corresponding to each band of the image signal, that is, for terrestrial, BS, and CS. Then, the memory 86 supplies the noise intensity calculation circuit 85 with a high-quality color bar image without noise corresponding to the band of the input image signal as necessary.

  The memory 87 stores the noise intensity supplied from the noise intensity calculation circuit 85 for each band of the input image signal. Thereby, when the bay 3 is upgraded, that is, when the bay 3 is collected by the device manufacturer, the device manufacturer also collects noise intensity data for each band of the input image signal stored in the memory 87. can do. Accordingly, by using the noise intensity data for each band of the collected input image signal, that is, by generating the student data using the noise intensity data from the teacher data and performing the above-described learning, the following bay 3 In this version upgrade, it is possible to obtain a tap coefficient capable of image conversion processing with higher image quality.

  Here, at the time of version upgrade of the bay 3, what is collected by the device maker is only required to have the memory 87 in which the noise intensity is stored. Therefore, the noise intensity calculation circuit 85 and the memory 86 are included in the television 1. That is, for example, the image signal processing circuit 14 may be provided.

  Further, the coefficient generation circuit 15 of FIG. 8 described above is configured by a one-chip IC. Note that each of the storage unit 71, the selection switch 72, the remote control radio wave reception circuit 73, and the reception noise detection unit 74 of the coefficient generation circuit 15 may be configured by a one-chip IC.

  FIG. 9 shows a color bar image of the input image signal as a test signal and a color bar image stored in the memory 86, which are used for noise intensity calculation of the noise intensity calculation circuit 85.

  The color bar image on the left side of FIG. 9 shows the color bar image of the input image signal. The color bar image on the right side of FIG. 9 shows the color bar image stored in the memory 86. A color bar image is an image in which colors such as red, blue, and yellow, and gray colors of various densities such as black, gray, and white are displayed for each area obtained by dividing the screen (entire image) into predetermined areas. is there. In FIG. 9, the difference in each color and the difference in each density are represented using a pattern or the like.

  In FIG. 9, the color bar image (left side of FIG. 9) of the input image signal is darker (lower) in overall brightness and poor in contrast than the color bar image (right side of FIG. 9) stored in the memory 86. It is (small). In addition, the color bar image (left side in FIG. 9) of the input image signal has a sharper boundary between the areas than the color bar image (right side in FIG. 9) stored in the memory 86. These differences are caused by the influence of noise in the input image signal. The apparatus manufacturer can know the data (data stored in the memory 87) obtained by the noise intensity calculation circuit 85 calculating the noise intensity of the input image signal when the bay 3 is collected. Therefore, for example, the device manufacturer statistically (for example, averages) the noise status of each band for each region (for example, Shinagawa Ward) and obtains a tap coefficient for each region, and performs image conversion processing on the input image signal. It is possible to customize the tap coefficient for each user.

  The data stored in the memory 87 is the data of the noise intensity calculated by the noise intensity calculation circuit 85. However, when the apparatus manufacturer collects the bay 3 so as to store the test signal itself of the input image signal. The noise intensity can be calculated on the device manufacturer side.

  Next, the image conversion process described with reference to FIG. 7 will be described again with reference to the flowchart of FIG.

  The processes in steps S21 to S26 except for step S24 in FIG. 10 are the same as the processes in steps S11 to S16 except for step S14 in FIG. In other words, in the processing of FIGS. 7 and 10, only step S14 of FIG. 7 is different from step S24 of FIG. 10 corresponding to step S14 of FIG. Therefore, the description of the processing of each step other than step S24 is omitted as appropriate.

  In step S24, the coefficient generation circuit 15 is selected by the ROM table selection process described later with reference to FIG. 11 as the tap coefficient stored in the address corresponding to the class code supplied from the class code generation circuit 34. The tap coefficient output from the ROM table is supplied (output) to the prediction calculation circuit 35.

  In step S25, the prediction calculation circuit 35 acquires the prediction tap output from the prediction tap extraction circuit 31 and the tap coefficient output from the coefficient generation circuit 15 in step S24, and uses the prediction tap and the tap coefficient. And performing a predetermined prediction calculation to obtain a true predicted value of the target pixel. Thereby, the prediction calculation circuit 35 outputs the pixel value (predicted value) of the pixel of interest, that is, the pixel value of the pixels constituting the second image signal.

  FIG. 11 is a flowchart for explaining the ROM table selection process of the coefficient generation circuit 15 executed together with the image conversion process of FIG.

  First, in step S41, the remote control radio wave reception circuit 72 of the coefficient generation circuit 15 (FIG. 8) determines whether or not an operation command has been received from the remote control 4. If it is determined in step S41 that an operation command has not been received from the remote controller 4, the process proceeds to step S42, and the selection switch 72 outputs the output of the ROM table 84 among the outputs of the ROM tables 81 to 84 of the storage unit 71, That is, the output of the default ROM table 84 is selected. In step S42, if the selection switch 72 has previously selected one of the outputs of the ROM tables 81 to 84, the selection switch 72 may select the output of the selected ROM table as it is. . And after the process of step S42, it returns to step S41.

  On the other hand, if it is determined in step S41 that an operation command has been received from the remote controller 4, the process proceeds to step S43, and the remote control radio wave receiving circuit 73 determines whether or not the operation command is a command representing a predetermined button. . Here, the predetermined button is a button that can determine the band of the input image signal, and is, for example, a terrestrial, BS, or CS switching button, or each channel button.

  If it is determined in step S43 that the received operation command is not a command representing a predetermined button, the process proceeds to step S42, and the selection switch 72 outputs the outputs of the ROM tables 81 to 84 of the storage unit 71 as described above. Of these, the output of the default ROM table 84 or the previous output is selected.

  On the other hand, if it is determined in step S43 that the received operation command is a command representing a predetermined button, the process proceeds to step S44, where the remote control radio wave receiving circuit 73 selects the received operation command as a selection switch 72 and a noise intensity calculation circuit. 85. Then, the selection switch 72 selects the output (tap coefficient) of the ROM table corresponding to the operation command supplied from the remote control radio wave receiving circuit 73 from the outputs of the ROM tables 81 to 83.

  In step S44, the noise intensity calculation circuit 85 determines the band of the input image signal based on the operation command supplied from the remote control radio wave reception circuit 73, and the color bar image corresponding to the determined band of the image signal. An image signal is read from the memory 86. The noise intensity calculation circuit 85 calculates the noise intensity of the image signal input from the tuner 13 from the read image signal of the color bar image and the image signal of the color bar image input from the tuner 13. Further, the noise intensity calculation circuit 85 outputs the calculated noise intensity to the memory 87, and returns to step S41.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 81 to 84 selected in the ROM table selection process is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the first embodiment, the coefficient generation circuit 15 receives the operation command transmitted from the remote controller 4 and determines the band of the input image signal based on the operation command. Further, the coefficient generation circuit 15 selects the output of the ROM tables 81 to 84 based on the band of the input image signal, thereby obtaining the tap coefficient optimum for the frequency band of the radio wave of the input image signal. Output (supply). Then, the image signal processing circuit 14 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimal tap coefficient, so that an optimal image is obtained for each frequency band of the radio wave of the input image signal. Conversion processing can be performed.

  Therefore, it is possible to perform optimal image conversion processing using (utilizing) the viewing characteristics of the user, that is, using the frequency band of the radio wave of the input image signal selected by the user.

  In the first embodiment, the memory 87 in which the noise intensity of the input image signal is calculated from the test signal of the input image signal and the test signal stored in the memory 86 is used when the bay 3 is upgraded. By collecting the information to the manufacturer, the device manufacturer obtains the radio wave condition (the user viewing characteristics) in the area where the user is viewing, and further learns the tap coefficient. More optimal image conversion processing can be performed.

(Second Embodiment)
FIG. 12 is a block diagram showing a configuration example of the second embodiment of the television 1 in FIG. Note that portions corresponding to those of the first embodiment in FIG. 2 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the television 1 in FIG. 12 is configured in the same manner as in the first embodiment except that a coefficient generation circuit 101 is provided instead of the coefficient generation circuit 15 in the first embodiment in FIG. .

  Also in the second embodiment, as in the first embodiment, the image signal processing circuit 14 performs an image conversion process for converting an image signal supplied from the tuner 13 into a high-quality image signal. .

  The image signal processing circuit 14 includes a class code corresponding to a class obtained by performing class classification according to the level distribution shape of the input image signal supplied from the tuner 13, and the image signal supplied from the tuner 13. Is supplied to the coefficient generation circuit 101. Similar to the first embodiment, the coefficient generation circuit 101 obtains a tap coefficient from the class code supplied from the image signal processing circuit 14 and supplies the tap coefficient to the image signal processing circuit 14. Then, the image signal processing circuit 14 generates a high quality image using the tap coefficient supplied from the coefficient generation circuit 101 and supplies it to the CRT 16.

  FIG. 13 is a block diagram showing a detailed configuration of the image signal processing circuit 14 of FIG. Note that portions corresponding to those in the first embodiment in FIG. 3 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the image signal processing circuit 14 of FIG. 13 is the same as that of the first embodiment except that the processing is performed using the coefficient generation circuit 101 instead of the coefficient generation circuit 15 in the first embodiment of FIG. It is constituted similarly.

  Similar to the first embodiment, the coefficient generation circuit 101 in the bay 3 stores the tap coefficient for each class obtained by learning, and further, from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the supplied class code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  FIG. 14 is a block diagram showing a detailed configuration example of the coefficient generation circuit 101 of FIG. Note that portions corresponding to those of the first embodiment in FIG. 8 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  The coefficient generation circuit 101 includes a reception noise detection unit 74, a storage unit 111, a selection switch 112, a channel (Ch) frequency detection unit 113, and a remote control radio wave reception circuit 114.

  The storage unit 111 includes a ROM table 121 for channel 1 (Ch. 1), a ROM table 122 for channel 6 (Ch. 6), a ROM table 123 for channel 42 (Ch. 42), and a default table. The ROM table 124 is used. Further, the channel frequency detection unit 113 includes a channel (Ch) frequency counting circuit 125 and a memory 126.

  The class code output from the class code generation circuit 34 (FIG. 13) is supplied to the ROM tables 121 to 124 of the storage unit 111. The storage unit 111 classifies according to the shape of the level distribution of the input image signal, and stores a table storing tap coefficients (prediction coefficients) obtained by learning in advance for each class for each predetermined type. . In other words, the storage unit 111 stores, for each predetermined type, a table learned using a set of teacher data and student data.

  In the second embodiment, the storage unit 111 stores a table in which tap coefficients are stored for each channel (broadcast station) of the input image signal, for example, channel 1, channel 6, and channel 42. Here, the table in which the tap coefficients are stored is three types of channel 1, channel 6, and channel 42. However, tables may be provided for other channels, and the types of tables stored in the storage unit 111 are also possible. Is not limited to the above three types.

  The ROM table 121 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using an image signal of channel 1 as an input image signal. In this learning, for example, an image signal of an HD image is used as teacher data, and an image signal of an SD image obtained by down-sampling the HD image and receiving the image signal transmitted through channel 1 is used as student data. be able to. As a result, it is possible to obtain a tap coefficient that can remove noise caused by high resolution and propagation in channel 1. Further, for example, the image signal of the SD image can be used as the teacher data, and the image signal of the SD image obtained by receiving the image signal obtained by sending the SD image through the channel 1 can be used as the student data. Thereby, it is possible to obtain a tap coefficient capable of removing noise generated by propagation in the channel 1.

  The ROM table 122 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using the image signal of the channel 6 as an input image signal. The ROM table 123 stores (stores) tap coefficients obtained by learning in advance for each class, which is suitable for performing image conversion processing using the image signal of the channel 42 as an input image signal. The teacher data used for learning the tap coefficient stored in the ROM table 122 or 123 can be the same data as the ROM table 121. In addition, the student data used for learning the tap coefficient stored in the ROM table 122 or 123 is the image signal sent on the channel 6 or the channel 42 instead of the image signal sent on the channel 1 in the learning of the ROM table 121. The data can be the same as that of the ROM table 121 except that.

  The ROM table 124 stores (stores) tap coefficients previously acquired by learning for each class when the input image signal is an image signal that does not correspond to any of the channel 1, the channel 6, and the channel 42. Here, the value of the tap coefficient for each class stored in the ROM table 124 is, for example, a value that is an intermediate value between the tap coefficients of the corresponding classes of the channel 1, channel 6, and channel 42, respectively. Or it is good also as a tap coefficient acquired by learning beforehand for every class by the image signal of other arbitrary channels.

  Each of the ROM tables 121 to 124 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 112.

  The selection switch 112 selects the output (tap coefficient) of the ROM table of the type associated with the operation command from the outputs of the ROM tables 121 to 124. That is, the selection switch 112 determines the channel of the input image signal based on the operation command supplied from the remote control radio wave receiving circuit 114. Then, the selection switch 112 selects one of the outputs (tap coefficients) of the ROM tables 121 to 124 based on the determined channel of the image signal, and selects the selected tap coefficient in the prediction calculation circuit 35 (FIG. 13). To supply. Here, since the tap coefficient output from the selection switch 112 is an optimum tap coefficient for the input image signal, it can be said that it is an optimization coefficient.

  The prediction calculation circuit 35 in FIG. 13 calculates an optimum estimated value by calculation based on the prediction formula of Formula (1) using the tap coefficient that is the output of the ROM table selected by the selection switch 112.

  As described above, the remote control radio wave reception circuit 114 receives an operation command transmitted wirelessly from the remote control 4. Then, the remote control radio wave reception circuit 114 supplies the received operation command to the selection switch 112, the noise intensity calculation circuit 85, and the channel frequency counting circuit 125.

  The channel frequency counting circuit 125 counts the frequency (channel selection frequency) at which a predetermined channel of the input image signal is selected based on the operation command supplied from the remote control radio wave receiving circuit 114. Here, the channel frequency counting circuit 125 reads the channel selection frequency for each channel stored in the memory 126, increments the read value by 1, and writes it in the same position as the read position in the memory 126.

  The memory 126 stores the channel selection frequency of the channel supplied from the channel frequency counting circuit 125 for each channel.

  Here, when the version of the bay 3 is upgraded, what is collected by the device maker is only required to have the memory 87 storing the noise intensity and the memory 126 storing the channel selection frequency. 85, the memory 86, and the channel selection frequency counting circuit 125 may be provided inside the television 1, that is, for example, in the image signal processing circuit 14.

  Further, the coefficient generation circuit 101 of FIG. 14 described above is configured by a one-chip IC. Note that each of the reception noise detection unit 74, the storage unit 111, the selection switch 112, the channel frequency detection unit 113, and the remote control radio wave reception circuit 114 may be configured by a one-chip IC.

  Image conversion processing performed by the image signal processing circuit 14 and the coefficient generation circuit 101 in FIG. 13 is the same as the image conversion processing described with reference to FIG. 10 in the first embodiment.

  Next, ROM table selection processing in the second embodiment will be described with reference to the flowchart of FIG.

  First, in step S51, the remote control radio wave reception circuit 114 of the coefficient generation circuit 101 (FIG. 14) determines whether or not an operation command has been received from the remote control 4. If it is determined in step S51 that an operation command has not been received from the remote controller 4, the process proceeds to step S52, and the selection switch 112 outputs the ROM table 124 out of the outputs from the ROM tables 121 to 124 in the storage unit 111. That is, the output of the default ROM table 124 is selected. In step S52, if the selection switch 112 has previously selected one of the outputs of the ROM tables 121 to 124, the output of the selected ROM table may be selected as it is. . And after the process of step S52, it returns to step S51.

  On the other hand, if it is determined in step S51 that an operation command has been received from the remote controller 4, the process proceeds to step S53, where the remote control radio wave reception circuit 114 determines whether the operation command is a command representing a predetermined button. . Here, the predetermined button is a button capable of discriminating a channel, for example, each channel button.

  If it is determined in step S53 that the received operation command is not a command representing a predetermined button, the process proceeds to step S52, and the selection switch 112 outputs the outputs of the ROM tables 121 to 124 of the storage unit 111 as described above. Of these, the output of the ROM table 124 or the previous output is selected.

  On the other hand, if it is determined in step S53 that the received operation command is a command representing a predetermined button, the process proceeds to step S54, where the remote control radio wave reception circuit 114 converts the received operation command into a noise intensity calculation circuit 85, a selection switch. 112 and the channel frequency counting circuit 125. The selection switch 112 selects the output (tap coefficient) of the ROM table corresponding to the operation command supplied from the remote control radio wave receiving circuit 114 from the outputs of the ROM tables 121 to 123.

  In step S54, the noise intensity calculation circuit 85 determines the channel of the input image signal based on the operation command supplied from the remote control radio wave reception circuit 114, and outputs the image signal of the color bar image corresponding to the determined channel. , Read from the memory 86. The noise intensity calculation circuit 85 calculates the noise intensity of the image signal input from the tuner 13 from the read image signal of the color bar image and the image signal of the color bar image input from the tuner 13. Further, the noise intensity calculation circuit 85 outputs the calculated noise intensity to the memory 87.

  In step S 54, the channel frequency counting circuit 125 determines the channel of the input image signal based on the operation command supplied from the remote control radio wave receiving circuit 114, and the channel selection frequency for each channel stored in the memory 126. Then, the channel selection frequency of the determined channel is read, the read value is incremented by 1, written in the same position as the read position in the memory 126, and the process returns to step S51.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 121 to 124 selected in the ROM table selection process is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the second embodiment, the coefficient generation circuit 101 receives the operation command transmitted from the remote controller 4 and determines the channel of the input image signal based on the operation command. Further, the coefficient generation circuit 101 outputs the optimum tap coefficient for each channel of the input image signal to the image signal processing circuit 14 by selecting the output of the ROM tables 121 to 124 based on the channel of the input image signal. (Supply). Then, the image signal processing circuit 14 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, and performs image conversion processing optimal for the channel of the input image signal. be able to. Note that if the radio wave conditions (output wattage, output location, etc.) of each broadcasting station and the area receiving the radio wave from the broadcasting station differ, the optimum tap coefficient for each broadcasting station (channel) of the input image signal will differ. It can be.

  Accordingly, it is possible to perform optimal image conversion processing by utilizing (utilizing) the viewing characteristics of the user, that is, by utilizing the channel of the input image signal selected by the user.

  In the second embodiment, since the frequency of the channel selected by the user is stored in the memory 126, when the device manufacturer collects it when the version of the bay 3 is upgraded, the device manufacturer views the user. You can know the frequency of the channel that is. In addition, the memory 126 can further store the viewing time for each channel, and in this case, the user can know the program that the user is interested in.

(Third embodiment)
FIG. 16 is a block diagram illustrating a configuration example of the third embodiment of the television 1 in FIG. 1. Note that portions corresponding to those of the first embodiment in FIG. 2 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the television 1 in FIG. 16 is provided with an image signal processing circuit 141 and a coefficient generation circuit 142 in place of the image signal processing circuit 14 and the coefficient generation circuit 15 in the first embodiment of FIG. The configuration is the same as in the first embodiment.

  Also in the third embodiment, similarly to the first embodiment, the image signal processing circuit 141 performs image conversion processing for converting an image signal supplied from the tuner 13 into a high-quality image signal. .

  The image signal processing circuit 141 includes a class code corresponding to a class obtained by performing class classification according to the level distribution shape of the input image signal supplied from the tuner 13, an image signal supplied from the tuner 13, and the like. Is supplied to the coefficient generation circuit 142. Similar to the first embodiment, the coefficient generation circuit 142 obtains a tap coefficient from the class code supplied from the image signal processing circuit 141 and supplies the tap coefficient to the image signal processing circuit 141. Then, the image signal processing circuit 141 generates a high-quality image using the tap coefficient supplied from the coefficient generation circuit 142 and supplies it to the CRT 16.

  FIG. 17 is a block diagram showing a detailed configuration of the image signal processing circuit 141 of FIG. Note that portions corresponding to those in the first embodiment in FIG. 3 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  In the image signal processing circuit 141 of FIG. 17, the image signal output from the tuner 13 is supplied to the resizing circuit 143. The resizing circuit 143 resizes (enlarges or reduces) the input image signal according to a predetermined resizing rate, and generates a resized image whose size has been changed.

  Here, the resizing rate in the resizing circuit 143 is controlled by the control circuit 18 (FIG. 16) based on the operation command supplied from the remote control radio wave receiving circuit 17. The remote control radio wave reception circuit 17 receives an operation command transmitted from the remote control 4 and corresponding to the user's zoom operation, and supplies it to the control circuit 18.

  As the resizing rate, for example, the same size as the size of the input image signal, that is, the size of the input image signal is not changed (no zooming), the same image as the input image with respect to the size of the input image signal, Interpolation or the like that reduces the vertical and horizontal sizes to ½ by thinning processing (referred to as small zoom) and an input image, for example, an image in a predetermined range of 1/2 size in the vertical and horizontal directions It is assumed that there are three types, that is, the same size as the input image (called zoom large). However, the resizing rate for small zoom and large zoom is not limited to the above-mentioned 1/2. The resize circuit 143 supplies the generated image signal of the resized image to each of the prediction tap extraction circuit 31 and the class tap extraction circuit 33.

  In the first embodiment of FIG. 3, the input image signal is also supplied to the coefficient generation circuit 15, but in the third embodiment, the input image signal is not supplied to the coefficient generation circuit 142.

  Similar to the first embodiment, the coefficient generation circuit 142 in the bay 3 stores the tap coefficient for each class obtained by learning, and further, from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the supplied class code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  FIG. 18 is a block diagram showing a detailed configuration example of the coefficient generation circuit 142 of FIG.

  The coefficient generation circuit 142 includes a storage unit 151, a selection switch 152, and a remote control radio wave reception circuit 153.

  The storage unit 151 includes a zoom-free ROM table 161, a zoom small ROM table 162, and a zoom large ROM table 163.

  The class code output from the class code generation circuit 34 (FIG. 17) is supplied to the ROM tables 161 to 163 of the storage unit 151. The storage unit 151 classifies according to the shape of the level distribution of the input image signal, and stores a table storing tap coefficients (prediction coefficients) obtained by learning in advance for each class for each predetermined type. . In other words, the storage unit 151 stores, for each predetermined type, a table learned by using different types of sample images.

  In the third embodiment, the storage unit 151 stores a table storing tap coefficients for each resizing rate of the input image signal, for example, no zoom, small zoom, and large zoom. Here, the table storing the tap coefficients is three types, that is, no zoom, small zoom, and large zoom. However, tables may be provided for other resizing ratios and stored in the storage unit 151. The type of table is not limited to the above three types.

  The ROM table 161 is acquired by learning in advance for each class, which is suitable when the image signal whose resizing rate is controlled by the control circuit 18 in the resizing circuit 143 in FIG. The stored tap coefficients are stored (stored). In this learning, for example, the image signal of the SD image can be used as teacher data, and the image signal of the SD image obtained by receiving the image signal transmitted from the SD image can be used as student data. Thereby, it is possible to obtain a tap coefficient capable of removing noise generated by propagation without zooming.

  The ROM table 162 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using an image signal whose resizing rate is controlled to a small zoom by the control circuit 18 as an input image signal. )is doing. The ROM table 163 stores tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using an image signal whose resizing rate is controlled to be large by the control circuit 18 as an input image signal. (Store). The teacher data used for learning the tap coefficient stored in the ROM table 162 or 163 can be an image signal of an SD image as in the case of learning in the ROM table 161. In addition, the student data employed for learning the tap coefficient stored in the ROM table 162 or 163 is the SD image obtained by receiving the image signal obtained by transmitting the image signal of the SD image of the teacher data at a small zoom or large zoom. It can be an image signal.

  Each of the ROM tables 161 to 163 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 152.

  The selection switch 152 selects the output (tap coefficient) of the ROM table of the type associated with the operation command from the outputs of the ROM tables 161 to 163. That is, the selection switch 152 determines the resizing rate controlled by the resizing circuit 151 of the image signal processing circuit 141 based on the operation command supplied from the remote control radio wave receiving circuit 153. The selection switch 152 selects one of the outputs (tap coefficients) of the ROM tables 161 to 163 based on the determined resizing rate, and supplies the selected tap coefficient to the prediction calculation circuit 35 (FIG. 17). To do. Here, since the tap coefficient output from the selection switch 152 is an optimum tap coefficient for the resizing rate of the input image signal, it can be said that it is an optimization coefficient.

  The prediction calculation circuit 35 of FIG. 17 calculates an optimum estimated value by calculation based on the prediction formula of Formula (1) using the tap coefficient that is the output of the ROM table selected by the selection switch 152.

  The image conversion processing performed by the image signal processing circuit 141 and the coefficient generation circuit 142 in FIG. 17 is the same as the image conversion processing described in FIG. 10 in the first embodiment.

  Next, ROM table selection processing in the third embodiment will be described with reference to the flowchart in FIG.

  First, in step S61, the remote control radio wave reception circuit 153 of the coefficient generation circuit 142 (FIG. 18) determines whether or not an operation command has been received from the remote control 4. If it is determined in step S61 that no operation command has been received from the remote controller 4, the process proceeds to step S62, and the selection switch 152 uses the output from the ROM tables 161 to 163 of the storage unit 151 as a default ROM table. The output of the ROM table 161 without zooming is selected. In step S62, if the selection switch 152 has previously selected one of the outputs of the ROM tables 161 to 163, the selection switch 152 may select the output of the selected ROM table as it is. . And after the process of step S62, it returns to step S61.

  On the other hand, if it is determined in step S61 that an operation command has been received from the remote controller 4, the process proceeds to step S63, and the remote control radio wave reception circuit 153 determines whether or not the operation command is a command representing a predetermined button. . Here, the predetermined button is, for example, a button for designating a resizing rate.

  When it is determined in step S63 that the received operation command is not a command representing a predetermined button, the process proceeds to step S62, and the selection switch 152 outputs the outputs of the ROM tables 161 to 163 in the storage unit 151 as described above. Of these, the output of the ROM table 161 or the previous output is selected.

  On the other hand, if it is determined in step S63 that the received operation command is a command representing a predetermined button, the process proceeds to step S64, and the remote control radio wave reception circuit 153 supplies the received operation command to the selection switch 152. Then, the selection switch 152 selects the output (tap coefficient) of the ROM table corresponding to the operation command supplied from the remote control radio wave receiving circuit 153 from among the outputs of the ROM tables 161 to 163, and returns to step S61. .

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 161 to 164 selected in the ROM table selection process is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the third embodiment, the coefficient generation circuit 142 receives an operation command transmitted from the remote controller 4, and when the input image signal is resized in the resizing circuit 143 based on the operation command. Determine the resizing rate. Further, the coefficient generation circuit 142 selects (outputs) the tap coefficient optimum for the resizing rate of the input image signal to the image signal processing circuit 141 by selecting the output of the ROM tables 161 to 164 based on the resizing rate. To do. Then, the image signal processing circuit 141 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that an optimum image conversion process is performed for each resizing rate of the input image signal. It can be performed.

  Accordingly, it is possible to perform optimal image conversion processing using (using) the user's viewing characteristics, that is, using the resizing rate selected by the user.

(Fourth embodiment)
FIG. 20 is a block diagram showing a configuration example of the fourth embodiment of the television 1 in FIG. Note that portions corresponding to those of the first embodiment in FIG. 2 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  The television 1 in FIG. 20 is provided with an image signal input unit 171 having an input terminal 172 in place of the tuner 13 constituting the image input unit 11 in FIG. Further, an image signal processing circuit 173 is provided in place of the image signal processing circuit 14 in FIG. 2, and a coefficient generation circuit 174 is provided in place of the coefficient generation circuit 15.

  The image signal input unit 171 is provided with an input terminal 172 for inputting an image signal from an external device. For example, a DVD (Digital Versatile Disc) device 181 is connected to the input terminal 172, and an image signal output when a DVD is reproduced on the DVD device 181 is input to the image signal processing circuit 173 via the input terminal 172. Supplied.

  In the fourth embodiment, as in the first embodiment, the image signal processing circuit 173 converts the image signal (input image signal) supplied from the input terminal 172 into a high-quality image signal. Processing shall be performed.

  The image signal processing circuit 173 outputs to the coefficient generation circuit 174 a class code corresponding to a class obtained by performing class classification according to the level distribution shape of the input image signal supplied from the input terminal 172. Similar to the first embodiment, the coefficient generation circuit 174 obtains a tap coefficient from the class code supplied from the image signal processing circuit 173 and supplies the tap coefficient to the image signal processing circuit 173. Then, the image signal processing circuit 173 generates a high-quality image using the tap coefficient supplied from the coefficient generation circuit 174 and supplies it to the CRT 16.

  In FIG. 20, it is assumed that the remote controller 4 can operate the DVD device 181 in addition to the operation of the television 1. For example, the user can operate fast-forward reproduction, (normal) reproduction, slow reproduction (frame advance), etc. of the DVD device 181 by operating the remote controller 4.

  The external device connected to the input terminal 172 is not limited to the DVD device 181 and may be another device that reproduces a recording medium such as a video tape or a semiconductor memory.

  FIG. 21 is a block diagram showing a detailed configuration of the image signal processing circuit 173 of FIG. Note that portions corresponding to those in the first embodiment in FIG. 3 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  The image signal processing circuit 173 in FIG. 21 is the same as the image signal processing circuit 14 in the first embodiment in FIG. 3 except that the input image signal is not supplied to the coefficient generation circuit 174. In FIG. 21, a coefficient generation circuit 174 is provided in place of the coefficient generation circuit 15 in the first embodiment of FIG.

  Similar to the first embodiment, the coefficient generation circuit 174 in the bay 3 stores the tap coefficient for each class obtained by learning, and further, from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the supplied class code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  FIG. 22 is a block diagram showing a detailed configuration example of the coefficient generation circuit 174 of FIG.

  The coefficient generation circuit 174 includes a storage unit 191, a selection switch 192, a reproduction speed frequency detection unit 193, and a remote control radio wave reception circuit 194.

  The storage unit 191 includes a fast-forward playback ROM table 201 of the DVD device 181, a standard playback ROM table 202 of the DVD device 181, and a slow playback ROM table 203 of the DVD device 181. Further, the playback speed frequency detection unit 193 includes a playback speed frequency counting circuit 205 and a memory 206.

  The class code output from the class code generation circuit 34 (FIG. 21) is supplied to the ROM tables 201 to 203 of the storage unit 191. The storage unit 191 stores, for each predetermined type, a table that is classified into classes according to the shape of the level distribution of the input image signal and stores tap coefficients (prediction coefficients) obtained by learning in advance for each class. . In other words, the storage unit 191 stores, for each predetermined type, a table learned using each set of teacher data and student data.

  When reproducing a recording medium in the DVD device 181 or other recording medium reproducing device, noise superimposed on the image signal may differ depending on the reproducing speed.

  Therefore, in the fourth embodiment, the storage unit 191 stores a table storing tap coefficients for each playback speed when a DVD is played back on the DVD device 181. For example, the playback speed of a DVD is fast playback mode playback speed (hereinafter referred to as “fast forward”), standard (normal) mode playback speed (hereinafter referred to as “standard”), and slow playback (frame advance) mode playback speed (hereinafter referred to as “slow”). ) And store them in three different speeds. Here, the table in which the tap coefficients are stored is the above three types, but tables may be provided for other modes (speeds), and the types of tables stored in the storage unit 191 are the above three types. Not limited to types.

  The ROM table 201 stores tap coefficients acquired by learning in advance for each class, which is suitable when the DVD performs image conversion processing using an image signal reproduced by fast-forwarding as an input image signal in the DVD device 181 in FIG. (Store). In this learning, for example, an image signal of an HD image before recording is used as teacher data, and the HD image is down-converted and recorded on a DVD by the DVD device 181 and then reproduced by fast-forwarding. Can be used as student data. As a result, it is possible to obtain a tap coefficient capable of removing noise caused by high resolution and fast-forward playback when played back in fast-forward. Further, for example, an image signal of an SD image before recording is used as teacher data, and an image signal of an SD image obtained by recording the SD image on a DVD with the DVD device 181 and further reproducing it at a fast forward is used as student data. can do. As a result, it is possible to obtain a tap coefficient that can remove noise caused by reproduction by fast-forwarding.

  The ROM table 202 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing using an image signal reproduced as a standard as an input image signal. The ROM table 203 stores (stores) tap coefficients obtained by learning in advance for each class, which is suitable for performing image conversion processing using an image signal reproduced in slow as an input image signal. Note that the teacher data used for learning tap coefficients stored in the ROM table 202 or 203 can be the same data as the ROM table 201. In addition, the student data used for learning the tap coefficient stored in the ROM table 202 or 203 is obtained by reproducing in standard or slow instead of the image signal obtained by fast-forwarding in learning of the ROM table 201. The data can be the same as that of the ROM table 201 except that the image signal to be used is used.

  Each of the ROM tables 201 to 203 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 192.

  The selection switch 192 selects the output (tap coefficient) of the type of ROM table associated with the operation command from the outputs of the ROM tables 201 to 203. That is, the selection switch 192 determines the playback speed at which the DVD is played back on the DVD device 181 based on the operation command supplied from the remote control radio wave receiving circuit 194. Then, the selection switch 192 selects one of the outputs (tap coefficients) of the ROM tables 201 to 203 based on the determined reproduction speed, and supplies the selected tap coefficient to the prediction calculation circuit 35 (FIG. 21). To do. Here, the tap coefficient output from the selection switch 192 is an optimum coefficient because it is the optimum tap coefficient for the playback speed at which the DVD is played back on the DVD device 181.

  As described above, the remote control radio wave receiving circuit 194 receives an operation command transmitted wirelessly from the remote control 4. The remote control radio wave reception circuit 194 supplies the received operation command to the selection switch 192 and the reproduction speed frequency counting circuit 205.

  The playback speed frequency counting circuit 205 counts the playback speed frequency, which is the frequency of playback at each of the fast forward, standard, and slow playback speeds on the DVD device 181 based on the operation command supplied from the remote control radio wave receiving circuit 194. . That is, the playback speed frequency counting circuit 205 reads the playback speed frequency for each playback speed stored in the memory 206, increments the read value by 1, and writes it in the same position as the read position of the memory 206.

  The memory 206 stores the playback speed frequency of each playback speed supplied from the playback speed frequency counting circuit 205 for each playback speed.

  Here, when the version of the bay 3 is upgraded, what is collected by the device maker only needs to have at least the memory 206 in which the reproduction speed frequency is stored. That is, for example, the image signal processing circuit 173 may be provided.

  Further, the coefficient generation circuit 174 of FIG. 22 described above is configured by a one-chip IC. Note that each of the storage unit 191, the selection switch 192, the reproduction speed frequency detection unit 193, and the remote control radio wave reception circuit 194 may be configured by a one-chip IC.

  Further, in the above-described example, the DVD device 181 is connected to the input terminal 172. However, in addition to the DVD device 181, other recording / reproducing devices such as a VTR device are connected to the input terminal 172. Also good.

  When the recording / reproducing apparatus such as a VTR apparatus has a different recording mode such as a standard mode or a triple mode as a recording mode when recording a predetermined recording medium, the storage unit 191 in FIG. You may make it memorize | store the ROM table of the tap coefficient obtained by performing learning for every recording mode when an image signal is recorded.

  The image conversion processing performed by the image signal processing circuit 173 and the coefficient generation circuit 174 in FIG. 21 is the same as the image conversion processing described in FIG. 10 in the first embodiment.

  Next, a ROM table selection process according to the fourth embodiment will be described with reference to the flowchart of FIG.

  First, in step S71, the remote control radio wave reception circuit 194 of the coefficient generation circuit 174 (FIG. 22) determines whether or not an operation command has been received from the remote control 4. If it is determined in step S71 that an operation command has not been received from the remote controller 4, the process proceeds to step S72, and the selection switch 192 uses the output from the ROM tables 201 to 203 of the storage unit 191 as a default ROM table. The output of the standard ROM table 202 is selected. In step S72, if the output of the ROM table 201 to 203 has been selected before, the selection switch 192 may select the output of the selected ROM table as it is. . And after the process of step S72, it returns to step S71.

  On the other hand, if it is determined in step S71 that an operation command has been received from the remote controller 4, the process proceeds to step S73, and the remote control radio wave reception circuit 194 determines whether or not the operation command is a command representing a predetermined button. . Here, the predetermined button is, for example, a button for designating fast forward, reproduction, and slow.

  If it is determined in step S73 that the received operation command is not a command representing a predetermined button, the process proceeds to step S72, and as described above, the selection switch 192 outputs the outputs of the ROM tables 201 to 203 in the storage unit 191. Of these, the output of the ROM table 202 or the previous output is selected.

  On the other hand, if it is determined in step S73 that the received operation command is a command representing a predetermined button, the process proceeds to step S74, and the remote control radio wave reception circuit 194 selects the received operation command as a selection switch 192 and a reproduction speed frequency count. This is supplied to the circuit 205. The selection switch 192 selects a ROM table output (tap coefficient) corresponding to the operation command from the outputs of the ROM tables 201 to 203.

  In step S74, the reproduction speed frequency counting circuit 205 determines the reproduction speed of the input image signal based on the operation command supplied from the remote control radio wave reception circuit 194, and reproduces each reproduction speed stored in the memory 206. The playback speed frequency of the determined playback speed is read from the speed selection frequency, the read value is incremented by 1, written in the same position as the read position in the memory 206, and the process returns to step S71.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 201 to 203 selected in the ROM table selection processing is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the fourth embodiment, the coefficient generation circuit 174 receives the operation command transmitted from the remote controller 4, and based on the operation command, sets the reproduction speed at which the DVD is reproduced in the DVD device 181. Determine. Also, the coefficient generation circuit 174 selects (outputs) the tap coefficients optimum for the reproduction speed of the input image signal to the image signal processing circuit 173 by selecting the output of the ROM tables 201 to 203 based on the reproduction speed. To do. The image signal processing circuit 173 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that an optimum image conversion process is performed for each reproduction speed of the input image signal. It can be performed.

  Accordingly, it is possible to perform optimal image conversion processing using (utilizing) the viewing characteristics of the user, that is, using the reproduction speed selected by the user.

  In the fourth embodiment, since the DVD playback speed frequency of the DVD device 181 selected by the user is stored in the memory 206, when the device manufacturer collects it when the bay 3 is upgraded, the device manufacturer Can know the reproduction speed frequency at which the user reproduces the DVD device.

(Fifth embodiment)
FIG. 24 is a block diagram illustrating a configuration example of the fifth embodiment of the television 1 in FIG. 1. Note that portions corresponding to those of the first embodiment in FIG. 2 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the television 1 in FIG. 24 is configured in the same manner as in the first embodiment except that a coefficient generation circuit 211 is provided instead of the coefficient generation circuit 15 in the first embodiment in FIG. .

  Also in the fifth embodiment, as in the first embodiment, the image signal processing circuit 14 performs an image conversion process for converting an input image signal supplied from the tuner 13 into a high-quality image signal. To do.

  The image signal processing circuit 14 includes a class code corresponding to a class obtained by performing class classification according to the shape of the level distribution of the input image signal supplied from the tuner 13, and the input image signal supplied from the tuner 13. Is output to the coefficient generation circuit 211. Similar to the first embodiment, the coefficient generation circuit 211 obtains a tap coefficient from the class code supplied from the image signal processing circuit 14 and supplies the tap coefficient to the image signal processing circuit 14. Then, the image signal processing circuit 14 generates a high-quality image using the tap coefficient supplied from the coefficient generation circuit 211 and supplies it to the CRT 16.

  FIG. 25 is a block diagram showing a detailed configuration of the image signal processing circuit 14 of FIG. Note that portions corresponding to those in the first embodiment in FIG. 3 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the image signal processing circuit 14 of FIG. 25 is the same as that of the first embodiment except that the processing is performed using the coefficient generation circuit 211 instead of the coefficient generation circuit 15 in the first embodiment of FIG. It is constituted similarly.

  Similar to the first embodiment, the coefficient generation circuit 211 in the bay 3 stores the tap coefficient for each class obtained by learning, and further, from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the supplied class code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  FIG. 26 is a block diagram showing a detailed configuration example of the coefficient generation circuit 211 of FIG.

  The coefficient generation circuit 211 includes a storage unit 221, a selection switch 222, a learning circuit 223, a memory 224, and a local noise detection unit 225.

  The storage unit 221 includes a ROM table 231 for strong noise, a ROM table 232 for medium noise, a ROM table 233 for low noise, and a ROM table 234 for default. Further, the local noise detection unit 225 includes a local noise detection circuit 235 and a memory 236.

  The class code output from the class code generation circuit 34 (FIG. 25) is supplied to the ROM tables 231 to 234 of the storage unit 221. The storage unit 221 stores, for each predetermined type, a table that is classified according to the shape of the level distribution of the input image signal and stores tap coefficients (prediction coefficients) that are acquired in advance for each class by learning. . In other words, the storage unit 221 stores, for each predetermined type, a table learned using each set of teacher data and student data.

  In the fifth embodiment, the storage unit 221 uses a table storing tap coefficients as local noise (hereinafter referred to as local noise) generated around the television 1 such as strong noise, medium noise, and low noise. It is memorized for each intensity. Here, the table in which the tap coefficients are stored has three types of noise intensity: strong noise, medium noise, and low noise, but the noise intensity may be further classified and stored in the storage unit 221. The type of table is not limited to the above three types.

  In addition, the storage unit 221 stores a table in which tap coefficients learned from a set of an image signal to which noise of different intensity is added and an image signal to which noise is not added, which are supplied from the learning circuit 223, are stored. Update for each noise intensity.

  In the ROM tables 231 to 233, when the table is updated with the tap coefficient supplied from the learning circuit 223, the local noise detection circuit 235 has the detected noise intensity belonging to strong noise, medium noise, or low noise. In accordance with the determination result, the learning circuit 223 supplies designation information for designating the ROM table whose stored contents are to be updated by the tap coefficient obtained by learning to any of the ROM tables 231 to 233. Then, the ROM table designated by the designation information from the local noise detection circuit 235 among the ROM tables 231 to 233 updates the stored tap coefficient with the tap coefficient output from the learning circuit 223.

  The ROM table 231 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing of an input image signal when the intensity of local noise is strong noise. . In this learning, for example, an image signal of an HD image is used as teacher data, and an image signal of an SD image obtained by down-converting the HD image and adding strong noise (for example, white noise) is used as student data. can do. Thereby, it is possible to obtain a tap coefficient capable of increasing the resolution and removing noise. Further, for example, an image signal of an SD image can be used as teacher data, and an image signal of an SD image obtained by adding strong noise to the image signal of the SD image can be used as student data. Thereby, the tap coefficient which can perform noise removal can be obtained.

  When the ROM table 231 receives from the local noise detection circuit 235 designation information for designating a ROM table whose stored contents are to be updated by the tap coefficient supplied from the learning circuit 223, that is, detected by the local noise detection circuit 235. If the intensity of the local noise is strong noise, the ROM table 231 updates the stored content by overwriting the tap coefficient output from the learning circuit 223.

  The ROM table 232 stores (stores) tap coefficients obtained by learning in advance for each class, which is suitable for performing image conversion processing of an input image signal when the intensity of local noise is medium noise. . Here, the teacher data used for learning the tap coefficient stored in the ROM table 232 can be the same data as the ROM table 231. The student data used for learning the tap coefficient stored in the ROM table 232 is an image obtained by adding medium noise instead of an image signal obtained by adding strong noise in learning of the ROM table 231. The data can be the same as in the ROM table 231 except that the signal is used.

  Further, when the ROM table 232 receives specification information from the local noise detection circuit 235 for designating a ROM table whose storage contents are to be updated by the tap coefficient supplied from the learning circuit 223, that is, detected by the local noise detection circuit 235. When the intensity of the local noise is medium noise, the ROM table 232 updates the stored content by overwriting the tap coefficient output from the learning circuit 223.

  The ROM table 233 stores (stores) tap coefficients acquired by learning in advance for each class, which is suitable for performing image conversion processing of an input image signal when the intensity of local noise is low noise. Yes. Here, the teacher data used for learning the tap coefficient stored in the ROM table 233 can be the same data as the ROM table 231. The student data used for learning the tap coefficient stored in the ROM table 233 is an image obtained by adding low noise instead of an image signal obtained by adding strong noise in the learning of the ROM table 231. The data can be the same as in the ROM table 231 except that the signal is used.

  Further, when the ROM table 233 receives designation information from the local noise detection circuit 235 that designates a ROM table whose stored contents are to be updated by the tap coefficient supplied from the learning circuit 223, that is, detected by the local noise detection circuit 235. When the intensity of the local noise is low noise, the ROM table 233 updates the stored content by overwriting the tap coefficient output from the learning circuit 223.

  The ROM table 234 stores (stores) tap coefficients acquired by learning in advance for each class when the intensity of local noise does not correspond to any of strong noise, medium noise, and low noise. The value of the tap coefficient for each class stored in the ROM table 234 can be obtained by adopting, for example, an image signal without adding noise as teacher data and student data. That is, an image signal of an HD image can be used as teacher data, and an image signal of an SD image obtained by down-converting the HD image can be used as student data.

  Each of the ROM tables 231 to 234 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 222.

  The selection switch 222 outputs, based on the noise intensity detected by the local noise detection circuit 235, an output (a tap coefficient) of a ROM table of a type associated with the noise intensity from among the outputs of the ROM tables 231 to 234. ) Is selected. In other words, the selection switch 232 selects one of the outputs (tap coefficients) of the ROM tables 231 to 234 based on the intensity of noise supplied from the local noise detection circuit 235, and the selected tap coefficient is predicted by the calculation circuit. 35 (FIG. 25). Here, since the tap coefficient output from the selection switch 232 is an optimum tap coefficient for the input image signal, it can be said that it is an optimization coefficient.

  The learning circuit 223 uses the image signal supplied from the tuner 13 as student data and performs learning for calculating the tap coefficient for each class using the image signal stored in the memory 224 as teacher data. Then, the learning circuit 223 supplies the tap coefficients for each class obtained by learning to the ROM tables 231 to 233. That is, the learning circuit 223 calculates a tap coefficient to be stored in one of the ROM tables 231 to 233 of the storage unit 221 from the image signal supplied from the tuner 13 and the image signal stored in the memory 224.

  The memory 224 stores an image signal (test signal) as teacher data corresponding to the image signal (student data) supplied from the tuner 13. The memory 224 stores, for example, an HD image corresponding to an image signal of a broadcast program to be broadcast from now on downloaded via a network such as the Internet, and an SD image obtained by down-converting the HD image. When an image signal as teacher data is downloaded to the memory 224, specific information for specifying the downloaded image signal (such as a broadcast channel and broadcast date / time of the image signal) is downloaded together with the image signal. The learning circuit 223 recognizes the teacher data corresponding to the student data supplied from the tuner 13 from the broadcast time and the image signal stored in the memory 224 based on the specific information, and determines the tap coefficient. Do learning.

  The local noise detection circuit 235 receives ambient radio waves and detects the intensity of local noise generated around the television 1. Here, examples of devices that generate noise around the television 1 include a microwave oven and other electronic devices. The local noise detection circuit 235 detects, for example, all radio waves other than the remote controller 4 as local noise generated around the television 1. In the fifth embodiment, there are three types of noise intensity: strong noise, medium noise, and low noise. Therefore, the local noise detection circuit 235 determines whether the detected noise intensity belongs to strong noise, medium noise, or low noise. Then, as described above, the local noise detection circuit 235 uses the ROM table 231 to specify the designation information for designating the ROM table whose storage contents are to be updated by the tap coefficient obtained by the learning by the learning circuit 223 according to the determination result. To 233.

  Further, the local noise detection circuit 235 supplies a determination result of whether the detected local noise intensity belongs to strong noise, medium noise, or low noise to the memory 236 together with the detected time (including date). .

  The memory 236 stores the determination result, which is supplied from the local noise detection circuit 235, whether the intensity of the local noise belongs to strong noise, medium noise, or low noise, and the time when the local noise is detected. .

  FIG. 27 is a block diagram illustrating a configuration example of the learning circuit 223 of FIG.

  The learning circuit 223 of FIG. 27 includes from the teacher data storage unit 241 to the tap coefficient calculation unit 247 that perform the same processing as the teacher data storage unit 52 and the student data storage unit 54 to the tap coefficient calculation unit 59 of the learning device of FIG. Composed. However, student data is supplied from the tuner 13 to the student data storage unit 242, and teacher data corresponding to the student data is supplied from the memory 224 to the teacher data 241. Other than that, the teacher data storage unit 241 to the tap coefficient calculation unit 247 of FIG. 27 perform the same processes as the teacher data storage unit 52 and the student data storage unit 54 to the tap coefficient calculation unit 59 of FIG.

  The image conversion processing performed by the image signal processing circuit 14 and the coefficient generation circuit 211 in FIG. 25 is the same as the image conversion processing described in FIG. 10 in the first embodiment.

  Next, the ROM table selection process in the fifth embodiment will be described with reference to the flowchart in FIG.

  First, in step S81, the local noise detection circuit 235 of the coefficient generation circuit 211 (FIG. 26) determines whether or not local noise has been detected. If it is determined in step S81 that local noise has not been detected, the process proceeds to step S82, where the selection switch 222 outputs the ROM table 234 out of the ROM tables 231 to 234 of the storage unit 221, ie, the default. The output of the ROM table 234 is selected. And after the process of step S82, it returns to step S81.

  On the other hand, if it is determined in step S81 that local noise has been detected, the process proceeds to step S83, and the local noise detection circuit 235 supplies the noise intensity of the detected local noise to the selection switch 222. The selection switch 222 determines whether the noise intensity supplied from the local noise detection circuit 235 belongs to strong noise, medium noise, or low noise. Then, the selection switch 222 selects the output (tap coefficient) of the ROM table corresponding to the determination result from the outputs of the ROM tables 231 to 233.

  In step S83, the local noise detection circuit 235 determines whether the noise intensity belongs to strong noise, medium noise, or low noise, and stores the stored content by the tap coefficient obtained by learning by the learning circuit 223. The designation information designating the ROM table to be updated is supplied to any of the ROM tables 231 to 233 according to the determination result, and the process proceeds to step S84.

  In step S84, the learning circuit 223 uses the image signal supplied from the tuner 13 as student data and starts learning to calculate a tap coefficient for each class using the image signal stored in the memory 224 as teacher data. Then, the process proceeds to step S85.

  In step S85, the local noise detection circuit 235 determines whether there is a change in the intensity of noise detected by the local noise detection circuit 235. In step S85, the process of step S85 is repeated until it is determined that the detected noise intensity has changed. That is, the learning circuit 223 continues to learn the ROM table specified in step S83 until the detected noise intensity changes.

  If it is determined in step S85 that there is a change in the detected noise intensity, the process proceeds to step S86, and the learning circuit 223 designates a ROM table whose stored contents are to be updated with the tap coefficient obtained by learning by the learning circuit 223. The stored information is updated by overwriting the ROM coefficient supplied from the local noise detection circuit 235 with the tap coefficient output from the learning circuit 223, and the process returns to step S81.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 231 to 234 selected in the ROM table selection process is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the fifth embodiment, the coefficient generation circuit 211 detects local noise, and selects the output of the ROM tables 231 to 234 based on the intensity of the noise, thereby reducing the noise of the local noise. A tap coefficient optimum for the intensity is output (supplied) to the image signal processing circuit 141. Then, the image signal processing circuit 14 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that an image conversion process optimum for local noise can be performed. .

  Therefore, it is possible to perform optimal image conversion processing using (using) the viewing characteristics of the user, that is, according to the environment where the user is viewing.

(Sixth embodiment)
FIG. 29 is a block diagram illustrating a configuration example of the sixth embodiment of the television 1 in FIG. 1. Note that portions corresponding to those in the first to fifth embodiments described above are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

  In the television 1 of FIG. 29, the image signal input unit 250 is provided with three input terminals 251 to 253 for inputting an image signal (image source) from an external device. For example, a DVD device 181 is connected to the input terminal 251. A VTR device 256 is connected to the input terminal 252, and a VTR device 257 is connected to the input terminal 253. Image signals input from external devices connected to the input terminals 251 to 253 are supplied to the input selection switch 254. The input terminals are not limited to the three input terminals 251 to 253.

  The user operates the remote controller 4 to select an input from any of the input terminals 251 to 253. That is, the user selects whether the image signal output from the DVD device 181, VTR device 256, or VTR device 257 is displayed on the CRT 15. The remote controller 4 transmits to the television 1 an operation command corresponding to the user's operation, that is, a command (hereinafter referred to as a selection command) indicating which of the input terminals 251 to 253 an input is selected.

  In addition to the operation of the television 1, the remote control 4 is assumed to be able to operate the DVD device 181, the VTR device 256, and the VTR device 257 in the same manner as in the fourth embodiment. That is, by operating the remote controller 4, the user can also select the input terminals 251 to 253 of the television 1 and operate the device connected to the selected input terminal. Further, when the user operates the device connected to the input terminals 251 to 253, the remote controller 4 together with the operation command, the manufacturer name or model name (model) of the device connected to the selected input terminal. It is assumed that a signal (command) including such information (hereinafter referred to as connection device information) can also be transmitted to the television 1. An operation command or the like transmitted from the remote control 4 is received by the remote control radio wave receiving circuit 17.

  The remote control radio wave reception circuit 17 receives the selection command transmitted from the remote control 4 and supplies it to the control circuit 18.

  In response to the selection command supplied from the remote control radio wave reception circuit 17, the control circuit 18 sends the image signal of the input terminal represented by the selection command among the input terminals 251 to 253 to the input selection switch 254 to the input selection switch 254. Let them choose.

  The input selection switch 254 selects an image signal from a predetermined input terminal among the input terminals 251 to 253 under the control of the control circuit 18. Then, the input selection switch 254 supplies the selected image signal to the image signal processing circuit 173.

  Also in the sixth embodiment, as in the first embodiment, the image signal processing circuit 173 performs an image conversion process for converting an image signal supplied from the input selection switch 254 into a high-quality image signal. And

  The image signal processing circuit 173 outputs to the coefficient generation circuit 255 a class code corresponding to a class obtained by performing class classification according to the level distribution shape of the input image signal supplied from the input selection switch 254 and the like. . Similar to the first embodiment, the coefficient generation circuit 255 calculates a tap coefficient from the class code supplied from the image signal processing circuit 173 and supplies the tap coefficient to the image signal processing circuit 173. Then, the image signal processing circuit 173 generates a high-quality image using the tap coefficient supplied from the coefficient generation circuit 255 and supplies it to the CRT 16.

  FIG. 30 is a block diagram showing a detailed configuration of the image signal processing circuit 173 of FIG. Note that portions corresponding to those of the fourth embodiment in FIG. 21 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  The image signal processing circuit 173 in FIG. 30 has the same configuration as that of the fourth embodiment except that the processing is performed using the coefficient generation circuit 255 instead of the coefficient generation circuit 174 in the fourth embodiment of FIG. Has been.

  Similar to the fourth embodiment, the coefficient generation circuit 255 in the bay 3 stores the tap coefficients for each class obtained by learning, and further, from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the supplied class code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  FIG. 31 is a block diagram showing a detailed configuration example of the coefficient generation circuit 255 of FIG.

  The coefficient generation circuit 255 includes a storage unit 261, a selection switch 262, an image source detection unit 263, and a remote control radio wave reception circuit 264.

  The storage unit 261 includes a ROM table 271 for the input terminal 251 (input 1), a ROM table 272 for the input terminal 252 (input 2), and a ROM table 273 for the input terminal 253 (input 3). Yes. Further, the image source detection unit 263 includes an image source selection frequency counting circuit 275 and a memory 276.

  The class code output from the class code generation circuit 34 (FIG. 30) is supplied to the ROM tables 271 to 273 of the storage unit 261. The storage unit 261 classifies according to the shape of the level distribution of the input image signal, and stores a table storing tap coefficients (prediction coefficients) obtained by learning in advance for each class for each predetermined type. . In other words, the storage unit 261 stores, for each predetermined type, a table learned using each set of teacher data and student data.

  In the sixth embodiment, the storage unit 261 stores a table storing tap coefficients for each of the input terminals 251 to 253. In other words, the ROM table 271 for the input terminal 251, the ROM table 272 for the input terminal 252, and the ROM table 273 for the input terminal 253 are stored separately. Here, the DVD device 181 is connected to the input terminal 251, and the VTR devices 256 and 257 are connected to the input terminals 252 and 253, respectively. Therefore, each of the ROM tables 271 to 273 can be referred to as a tap coefficient table depending on the type of a recording medium such as a DVD or a video tape. For example, when an image signal recorded on a DVD (image signal source) is reproduced, block distortion due to MPEG coding may occur in the image signal. Further, for example, when an image signal recorded on a video tape (image signal source) is reproduced, distortion specific to the magnetic reproduction system may occur in the image signal. Thus, since the noise generated in the image signal differs depending on the source of the image signal, the storage unit 261 stores a table in which the tap coefficient is stored for each source of the image signal. Further, even with a VTR device, there is a possibility that inherent noise may be added depending on, for example, a manufacturer that manufactures the VTR device. Therefore, the storage unit 261 stores a table in which tap coefficients are stored for each type of manufacturer such as a VTR device.

  Here, since the television 1 is configured with three input terminals 251 to 253, it is configured with three ROM tables 271 to 273. However, when there are other input terminals, The ROM table can also be configured for the input terminals.

  The ROM table 271 is a tap acquired by learning in advance for each class, which is suitable for performing image conversion processing using the input selection switch 254 as an image signal from the DVD device 181 connected to the input terminal 251 as an input image signal. Coefficients are stored (stored). Therefore, in this learning, for example, an image signal of an HD image before DVD recording is used as teacher data, and an image obtained by playing back an SD image recorded on a DVD by MPEG encoding by downsampling the HD image. The signal can be student data. Thereby, it is possible to obtain a tap coefficient capable of increasing the resolution and removing the block distortion in DVD reproduction. In addition, for example, an image signal of an SD image obtained by down-sampling an HD image before DVD recording is used as teacher data, and an image signal obtained by reproducing an SD image recorded on a DVD by MPEG encoding is used as student data. You can also. Thereby, it is possible to obtain a tap coefficient capable of performing block distortion removal in DVD reproduction.

  The ROM table 272 is a tap acquired by learning in advance for each class, which is suitable for performing an image conversion process using an image signal from the VTR device 256 connected to the input terminal 252 as an input image signal in the input selection switch 254. Coefficients are stored (stored). The ROM table 273 is acquired by learning in advance for each class, which is suitable for performing image conversion processing using the input selection switch 254 as an image signal from the VTR device 257 connected to the input terminal 253 as an input image signal. The tap coefficient is stored (stored). Here, the teacher data used for learning the tap coefficient stored in the ROM table 272 or 273 is the image signal of the HD image before recording on the video tape or the SD image obtained by down-sampling the HD image before recording on the video tape. It can be an image signal. In addition, the student data used for learning the tap coefficient stored in the ROM table 272 or 273 is a video tape instead of the image signal obtained by reproducing the SD image recorded on the DVD in the learning of the ROM table 271. Data similar to the ROM table 271 can be used except that an image signal obtained by reproducing a recorded SD image is used.

  Each of the ROM tables 271 to 273 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 262.

  The selection switch 262 selects the output (tap coefficient) of the ROM table of the type associated with the operation command from the outputs of the ROM tables 271 to 273. That is, the selection switch 262 determines which image signal of the input terminals 251 to 253 is selected based on the operation command supplied from the remote control radio wave receiving circuit 264. In other words, the selection switch 262 determines which playback device connected to the input terminals 251 to 253 is selected based on the operation command supplied from the remote control radio wave reception circuit 264. Then, the selection switch 262 selects one of the outputs (tap coefficients) of the ROM tables 271 to 273 based on the determination result, and supplies the selected tap coefficient to the prediction calculation circuit 35 (FIG. 30). Here, since the tap coefficient output from the selection switch 262 is an optimum tap coefficient for the selected image signal, it can be said that it is an optimization coefficient.

  The remote control radio wave reception circuit 264 receives an operation command transmitted from the remote control 4 by radio. The remote control radio wave receiving circuit 264 receives a signal (command) including connection device information transmitted from the remote control 4. The remote control radio wave reception circuit 264 supplies the received operation command and a signal (command) including connection device information to the selection switch 262 and the image source selection frequency counting circuit 275.

  The image source selection frequency counting circuit 275 is connected to the frequency at which the image signal input from the input terminals 251 to 253 is selected based on the operation command supplied from the remote control radio wave receiving circuit 264, that is, connected to the input terminals 251 to 253. The image source selection frequency, which is the frequency with which the selected playback device (image source) is selected, is counted. Here, the image source selection frequency counting circuit 275 obtains the device manufacturer name from the connected device information received from the remote control radio wave reception circuit 264, reads out the image source selection frequency stored for each manufacturer name in the memory 276, The read value is incremented by 1 and written in the same position as the read position in the memory 276.

  Therefore, the memory 276 can store the image source selection frequency supplied from the image source selection frequency counting circuit 275 for each apparatus manufacturer. The image source selection frequency supplied from the image source selection frequency counting circuit 275 may be stored for each model.

  Here, when the version of the bay 3 is upgraded, what is collected by the device maker only needs to have the memory 276 in which the image source selection frequency for each device maker is stored, so the image source selection frequency counting circuit 275 is required. May be provided inside the television 1, that is, for example, in the image signal processing circuit 173.

  Further, the coefficient generation circuit 255 of FIG. 31 described above is configured by a one-chip IC. Note that each of the storage unit 261, the selection switch 262, the image source detection unit 263, and the remote control radio wave reception circuit 264 may be configured by a one-chip IC.

  The image conversion processing performed by the image signal processing circuit 173 and the coefficient generation circuit 255 in FIG. 30 is the same as the image conversion processing described in FIG. 10 in the first embodiment.

  Next, the ROM table selection process in the sixth embodiment will be described with reference to the flowchart in FIG.

  First, in step S91, the remote control radio wave reception circuit 264 (FIG. 31) of the coefficient generation circuit 255 determines whether or not an operation command has been received from the remote control 4. If it is determined in step S91 that an operation command has not been received from the remote controller 4, the process proceeds to step S92, and the selection switch 262 selects the previous (previously selected) output from the ROM tables 271 to 273 of the storage unit 261. Select the output of the ROM table. And after the process of step S92, it returns to step S91.

  On the other hand, if it is determined in step S91 that an operation command has been received from the remote controller 4, the process proceeds to step S93, and the remote control radio wave reception circuit 264 determines whether or not the operation command is a command representing a predetermined button. . Here, the predetermined button is a button for designating one of the image signals from the input terminals 251 to 253, for example.

  If it is determined in step S93 that the received operation command is not a command representing a predetermined button, the process proceeds to step S92, and the selection switch 262 outputs the outputs of the ROM tables 271 to 273 of the storage unit 261 as described above. Among them, the output of the previous ROM table is selected.

  On the other hand, if it is determined in step S93 that the received operation command is a command representing a predetermined button, the process proceeds to step S94, where the remote control radio wave reception circuit 264 selects the received operation command as the selection switch 262 and the image source selection frequency. This is supplied to the counting circuit 275. The selection switch 262 selects the output (tap coefficient) of the ROM table corresponding to the operation command from the outputs of the ROM tables 271 to 273.

  Further, in step S94, the image source selection frequency counting circuit 275 reads out the image source selection frequency stored for each manufacturer name in the memory 276 based on the operation command supplied from the remote control radio wave reception circuit 264. The read value is incremented by 1, written in the same position as the read position in the memory 276, and the process returns to step S91.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 271 to 273 selected in the ROM table selection processing is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the sixth embodiment, the coefficient generation circuit 255 receives an operation command transmitted from the remote controller 4, and any image signal from the input terminals 251 to 253 is received based on the operation command. Further, it is determined what kind of device is selected (for example, a device manufacturer, a source of an image signal such as a DVD or a video tape) connected to the input terminal. Then, the coefficient generation circuit 255 performs image signal processing on the optimum tap coefficient for the image signal input from the input terminal, that is, for the source of the image signal such as the type of the device manufacturer and the recording medium connected to the input terminal. Output (supply) to the circuit 173. Accordingly, the image signal processing circuit 173 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that the source of the image signal such as the device manufacturer and the type of the recording medium Optimal image conversion processing can be performed for each.

  In the above-described example, the selection switch 262 outputs the outputs of the ROM tables 271 to 273 based on the operation command for selecting the image signal input from the input terminals 251 to 253 supplied from the remote control radio wave receiving circuit 264. Although selected, the remote control radio wave receiving circuit 264 receives a playback command (operation command) for playing back the recording media of the DVD device 181 and the VTR devices 256 and 257 connected to the input terminals 251 to 253. Thus, the selection switch 262 may select the output of the ROM tables 271 to 273 based on the reproduction command supplied from the remote control radio wave reception circuit 264.

  As described above, optimal image conversion processing can be performed using (utilizing) the viewing characteristics of the user, that is, using selection of the input terminal selected by the user.

  In the sixth embodiment, the image source selection frequency at which the device connected to the input terminals 251 to 253 is selected and the connected device information of the device are stored in the memory 276. When the bay 3 is collected, the collected device manufacturer can know the frequency with which the user uses the device connected to the television 1 and the connected device information. Using this, for example, an optimal ROM table can be designed for each device manufacturer or each device model.

(Seventh embodiment)
FIG. 33 is a block diagram illustrating a configuration example of the seventh embodiment of the television 1 in FIG. 1. Note that portions corresponding to those in the first to sixth embodiments described above are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

  In the television 1 of FIG. 33, in the image signal input unit 281, the DVD device 181, the VTR device 256, and the VTR device 257 are connected to the input terminals 251 to 253, respectively, as in the sixth embodiment. Each of the image signals input to the input terminals 251 to 253 is supplied to the input selection switch 254 and also to the coefficient generation circuit 283 in the bay 3.

  The input selection switch 254 selects an image signal from a predetermined input terminal among the input terminals 251 to 253 under the control of the control circuit 18. Then, the input selection switch 254 supplies the image signal of the selected input terminal to the image signal processing circuit 173.

  In addition, the tuner 13 of the image signal input unit 281 selects a television signal (on a channel selected by the user by operating the remote controller 4 based on the control of the control circuit 18 among the television signals supplied from the antenna 12. Select (Image signal). In addition, the tuner 13 supplies the selected television signal to the coefficient generation circuit 283 and the output terminal 291 of the image signal output unit 282.

  The output terminal 291 outputs the image signal supplied from the tuner 13 to each of the DVD device 181, the VTR device 256, and the VTR device 257. Accordingly, the image signal of the channel selected by the tuner 13 is supplied to the coefficient generation circuit 283 and also to each of the DVD device 181, the VTR device 256, and the VTR device 257. In each of the DVD device 181, the VTR device 256, and the VTR device 257, the image signal from the tuner 13 can be recorded on a predetermined recording medium.

  As in the case of the sixth embodiment, the user can operate the remote controller 4 to operate which image signal of the input terminals 251 to 253 is selected. That is, the user can select which output image signal of the DVD device 181, the VTR device 256, or the VTR device 257 is displayed on the CRT 15.

  Further, the user operates the remote controller 4 to record (record) the image signal supplied from the output terminal 291 on the recording medium in the DVD device 181, the VTR device 256, or the VTR device 257, and further record the recorded image. The signal can be reproduced.

  In this case, in the DVD device 181, VTR device 256, or VTR device 257 that is inputting the image signal selected by the input selection switch 254, it is reproduced from the recording medium (output from the output terminal 291 and recorded). The (read out) image signal can be supplied to the image processing circuit 173.

  That is, if an image signal supplied from the tuner 13 to the coefficient generation circuit 283 is called a primary image signal, it is supplied from the DVD device 181, VTR device 256, or VTR device 257 to the image signal processing circuit 173. The image signal can be said to be a secondary image signal after the primary image signal output from the tuner 13 is once recorded and reproduced.

  Also in the seventh embodiment, as in the first embodiment, the image signal processing circuit 173 performs image conversion processing for converting an image signal supplied from the input selection switch 254 into a high-quality image signal. And

  The image signal processing circuit 173 outputs to the coefficient generation circuit 283 a class code corresponding to the class obtained by performing class classification according to the shape such as the level distribution of the input image signal supplied from the input selection switch 254. . The coefficient generation circuit 283 obtains a tap coefficient from the class code supplied from the image signal processing circuit 173, and supplies the tap coefficient to the image signal processing circuit 173. Then, the image signal processing circuit 173 generates a high quality image using the tap coefficient supplied from the coefficient generation circuit 283 and supplies it to the CRT 16.

  FIG. 34 is a block diagram showing a detailed configuration of the image signal processing circuit 173 of FIG. Note that portions corresponding to those of the fourth embodiment in FIG. 21 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  The image signal processing circuit 173 in FIG. 34 is configured in the same manner as in the fourth embodiment, except that processing is performed using the coefficient generation circuit 283 instead of the coefficient generation circuit 174 in the fourth embodiment in FIG. Has been.

  Similar to the fourth embodiment, the class code is supplied from the class code generation circuit 34 to the coefficient generation circuit 283 in the bay 3 and the image signal is supplied from the tuner 13. The coefficient generation circuit 283 is supplied with an image signal from each of the input terminals 251 to 253.

  Similar to the first embodiment, the coefficient generation circuit 283 stores the tap coefficient for each class obtained by learning, and further, the class supplied from the class code generation circuit 34 among the stored tap coefficients. The tap coefficient stored in the address corresponding to the code (the tap coefficient of the class represented by the class code supplied from the class code generation circuit 34) is supplied (output) to the prediction arithmetic circuit 35.

  The coefficient generation circuit 283 uses the image signal supplied from the tuner 13 as teacher data and learns the tap coefficient by using the image signal supplied from each of the input terminals 251 to 253 as student data. The tap coefficient stored inside can be updated.

  FIG. 35 is a block diagram showing a detailed configuration example of the coefficient generation circuit 283 of FIG. Note that portions corresponding to those in the sixth embodiment in FIG. 31 are denoted with the same reference numerals, and description thereof will be omitted as appropriate.

  The coefficient generation circuit 283 includes a storage unit 261, a selection switch 262, a learning circuit 303, and a remote control radio wave reception circuit 304.

  The class code output from the class code generation circuit 34 (FIG. 34) is supplied to the ROM tables 271 to 273 of the storage unit 261. The storage unit 261 classifies according to the shape of the level distribution of the input image signal, and stores a table storing tap coefficients (prediction coefficients) obtained by learning in advance for each class for each predetermined type. . In other words, the storage unit 261 stores, for each predetermined type, a table learned using each set of teacher data and student data.

  In the seventh embodiment, the storage unit 261 stores a table in which tap coefficients are stored for each of the input terminals 251 to 253, as in the sixth embodiment. That is, the storage unit 261 stores the ROM table 271 for the input terminal 251, the ROM table 272 for the input terminal 252, and the ROM table 273 for the input terminal 253. Here, since the DVD device 181 is connected to the input terminal 251 and the VTR devices 256 and 257 are connected to the input terminals 252 and 253, respectively, the ROM table 271 is a ROM table for the DVD device 181. It can be said that the ROM table 272 is a ROM table for the VTR device 256, and the ROM table 273 is a ROM table for the VTR device 257.

  Further, the storage unit 261 is supplied from the tuner 13 with the image signal supplied from the DVD device 181, VTR device 256, or VTR device 257 selected by the input selection switch 254 supplied from the learning circuit 303. The table storing the tap coefficients learned by the set with the image signal is updated for each device (input terminal).

  The ROM table 271 is a tap acquired by learning in advance for each class, which is suitable for performing image conversion processing using the input selection switch 254 as an image signal from the DVD device 181 connected to the input terminal 251 as an input image signal. The coefficient is memorized. Here, the learning for obtaining the tap coefficient stored in the ROM table 271 is the same as in the sixth embodiment.

  The ROM table 272 is a tap acquired by learning in advance for each class, which is suitable for performing an image conversion process using an image signal from the VTR device 256 connected to the input terminal 252 as an input image signal in the input selection switch 254. The coefficient is memorized. Here, the learning for obtaining the tap coefficients stored in the ROM table 272 is the same as in the sixth embodiment.

  The ROM table 273 is a tap acquired by learning in advance for each class, which is suitable for performing an image conversion process using the image signal from the VTR device 257 connected to the input terminal 253 as the input image signal in the input selection switch 254. The coefficient is memorized. Here, the learning for obtaining the tap coefficient stored in the ROM table 273 is the same as in the sixth embodiment.

  Each of the ROM tables 271 to 273 outputs a tap coefficient corresponding to the class code supplied from the class code generation circuit 34 to the selection switch 262.

  The selection switch 262 selects the output (tap coefficient) of the ROM table of the type associated with the operation command from the outputs of the ROM tables 271 to 273. That is, the selection switch 262 determines which image signal of the input terminals 251 to 253 is selected based on the operation command supplied from the remote control radio wave receiving circuit 264. In other words, the selection switch 262 determines which playback device connected to the input terminals 251 to 253 is selected based on the operation command supplied from the remote control radio wave reception circuit 264. The selection switch 262 selects one of the outputs (tap coefficients) of the ROM tables 271 to 273 based on the determination result, and supplies the selected tap coefficient to the prediction calculation circuit 35 (FIG. 34). Here, since the tap coefficient output from the selection switch 262 is an optimal tap coefficient for the image signal input from the selected input terminal, it can be said that it is an optimization coefficient.

  The learning circuit 303 uses the image signal supplied from the DVD device 181, VTR device 256, or VTR device 257 as student data, and uses the image signal supplied from the tuner 13 as teacher data, and uses the DVD device 181, VTR device 256. Alternatively, at the time of recording (recording) an image signal in the VTR device 257, learning for calculating a tap coefficient for each class is performed in real time. In other words, when the DVD device 181, the VTR device 256, or the VTR device 257 records the image signal output from the tuner 13, the learning circuit 303 uses the image signal supplied from the tuner 13 as teacher data. At the same time, the image signal is recorded on a predetermined recording medium in the DVD device 181, VTR device 256, or VTR device 257, and learning is performed to calculate tap coefficients for each class in real time using the image signal as student data. . Then, the learning circuit 303 updates any one of the ROM tables 271 to 273 with the tap coefficient for each class obtained by learning. The learning circuit 303 has the same configuration as that in the fifth embodiment described with reference to FIG.

  The remote control radio wave reception circuit 264 receives an operation command transmitted from the remote control 4 by radio. The remote control radio wave receiving circuit 264 supplies the received operation command to the selection switch 262.

  The image conversion processing performed by the image signal processing circuit 173 and the coefficient generation circuit 283 in FIG. 34 is the same as the image conversion processing described in FIG. 10 in the first embodiment.

  Next, the ROM table selection process in the seventh embodiment will be described with reference to the flowchart in FIG.

  First, in step S <b> 101, the remote control radio wave reception circuit 304 of the coefficient generation circuit 283 determines whether or not an operation command has been received from the remote control 4. If it is determined in step S101 that an operation command has not been received from the remote controller 4, the process proceeds to step S102, where the selection switch 262 selects the previous (previously selected) output from the ROM tables 271 to 273 of the storage unit 261. Select the output of the ROM table. And after the process of step S102, it returns to step S101.

  On the other hand, if it is determined in step S101 that an operation command has been received from the remote controller 4, the process proceeds to step S103, and the remote control radio wave reception circuit 304 determines whether or not the operation command is a command representing a predetermined button. . Here, the predetermined button is a button for designating one of the image signals from the input terminals 251 to 253, for example.

  If it is determined in step S103 that the received operation command is not a command representing a predetermined button, the process proceeds to step S102, and as described above, the selection switch 262 outputs the outputs of the ROM tables 271 to 273 of the storage unit 261. Among them, the output of the previous ROM table is selected.

  On the other hand, if it is determined in step S103 that the received operation command is a command representing a predetermined button, the process proceeds to step S104, and the remote control radio wave receiving circuit 304 supplies the received operation command to the selection switch 262. Then, the selection switch 262 selects the output (tap coefficient) of the ROM table corresponding to the operation command from the outputs of the ROM tables 271 to 273, and returns to step S101.

  The ROM table selection process described above is executed in parallel with the image conversion process of FIG. 10 until the image conversion process of FIG. 10 is completed, that is, until it is determined that the input image signal is completed. Then, the output of any one of the ROM tables 271 to 273 selected in the ROM table selection processing is supplied to the prediction calculation circuit 35 as a tap coefficient corresponding to the class code of the input image signal in step S24 of FIG. (Output).

  As described above, in the seventh embodiment, the coefficient generation circuit 283 receives an operation command transmitted from the remote controller 4, and any input of the input terminals 251 to 253 is selected based on the operation command. The tap coefficient optimum for the image signal input from the input terminal is output (supplied) to the image signal processing circuit 173. The image signal processing circuit 173 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that the optimum image conversion for the image signal input from the input terminal is performed. Processing can be performed.

  Accordingly, it is possible to perform optimal image conversion processing using (utilizing) the viewing characteristics of the user, that is, using selection of the input terminal selected by the user.

  In the coefficient generation circuit 283 of FIG. 35, the tap coefficient can be updated as described above. A tap coefficient update process for updating the tap coefficient performed by the coefficient generation circuit 283 will be described with reference to the flowchart of FIG.

  First, in step S111, the DVD device 181, the VTR device 256, or the VTR device 257 starts reproduction of the image signal from the recording medium on which the image signal output from the tuner 13 is recorded, and then proceeds to step S112. move on. An image signal reproduced by the DVD device 181, the VTR device 256, or the VTR device 257 is input from the input terminal 251, 252, or 253 and supplied to the learning circuit 303.

  In step S112, the learning circuit 303 sets the image signal supplied from the DVD device 181, VTR device 256, or VTR device 257 as student data, and sets the image signal supplied from the tuner 13 as teacher data for each class. A normal equation of equation (8) is established, and the process proceeds to step S113.

  In step S113, the DVD device 181, the VTR device 256, or the VTR device 257 determines whether or not the process of recording the image signal supplied from the tuner 13 on a predetermined recording medium is completed. If it is determined in step S113 that the process of recording the image signal supplied from the tuner 13 on the predetermined recording medium has not been completed, the process of step S112 is continued. That is, in the learning circuit 303, the image signal supplied from the DVD device 181, the VTR device 256, or the VTR device 257 is used as student data, and the image signal supplied from the tuner 13 is used as teacher data. The normal equation is continued (added).

  On the other hand, if it is determined in step S113 that the process of recording the image signal supplied from the tuner 13 on the predetermined recording medium has been completed, the process proceeds to step S114, where the DVD device 181, the VTR device 256, or the VTR device 257 Then, the process of reproducing the image signal recorded on the recording medium started in step S111 is terminated, and the process proceeds to step S115.

  In step S115, the learning circuit 303 calculates the tap coefficient for each class by solving the normal equation of the equation (8) for each class, and proceeds to step S116.

  In step S116, the learning circuit 303 corresponds to the device of the DVD device 181, the VTR device 256, or the VTR device 257 that reproduces the image signal that is the student data in step S112 using the tap coefficient for each class obtained in step S115. The tap coefficient stored in the ROM table 271, 272, or 273 is updated by supplying the data to the ROM table 271, 272, or 273, and the process is terminated.

  The learning circuit 303 learns in real time from the image signal (student data) supplied from the DVD device 181, VTR device 256, or VTR device 257 and the image signal (teacher data) supplied from the tuner 13. Is performed (calculation of tap coefficient for each class), but the tuner is recorded in the teacher data storage unit 241 in the learning circuit 303 while the DVD device 181, VTR device 256, or VTR device 257 is recording. 13 may store (save) the image signal as teacher data output from the DVD 13 so that the learning is performed offline after the recording process in the DVD device 181, the VTR device 256, or the VTR device 257 is completed. .

(Eighth embodiment)
FIG. 38 is a block diagram showing a configuration example of the eighth embodiment of the television 1 in FIG. Note that portions corresponding to those in the first to seventh embodiments described above are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

  That is, the television 1 in FIG. 38 is provided with an image signal processing circuit 173 in place of the image signal processing circuit 14 in the first embodiment in FIG. 2 and a coefficient generation circuit 321 in place of the coefficient generation circuit 15. Yes.

  Also in the eighth embodiment, as in the first embodiment, the image signal processing circuit 173 performs image conversion processing for converting an image signal supplied from the tuner 13 into a high-quality image signal. .

  The image signal processing circuit 173 includes a class code corresponding to a class obtained by performing class classification according to the shape of the level distribution of the input image signal supplied from the tuner 13, and the input image signal supplied from the tuner 13. Is output to the coefficient generation circuit 321. The coefficient generation circuit 321 obtains a tap coefficient from the class code supplied from the image signal processing circuit 173 and supplies the tap coefficient to the image signal processing circuit 173, as in the first embodiment. Then, the image signal processing circuit 173 generates a high quality image using the tap coefficient supplied from the coefficient generation circuit 321 and supplies it to the CRT 16.

  FIG. 39 is a block diagram showing a detailed configuration of the image signal processing circuit 173 of FIG. Note that portions corresponding to those in the first embodiment in FIG. 3 are denoted by the same reference numerals, and description thereof is omitted as appropriate.

  That is, the image signal processing circuit 173 in FIG. 39 is the same as the image signal processing circuit 14 in the first embodiment in FIG. 3 except that the input image signal is not supplied to the coefficient generation circuit 321. In FIG. 39, a coefficient generating circuit 321 is provided in place of the coefficient generating circuit 15 in the first embodiment of FIG.

  In the first embodiment, the coefficient generation circuit 15 in FIG. 3 stores the tap coefficient for each class obtained in advance by learning. However, in the coefficient generation circuit 321 in the eighth embodiment, for example, It is possible to generate a tap coefficient for each class that can obtain an image with a desired image quality from the seed coefficient data that becomes the seed of the tap coefficient and a predetermined parameter.

  Therefore, the coefficient generation circuit 321 stores seed coefficient data for each parameter value, and further stores the seed coefficient data in an address corresponding to the class code supplied from the class code generation circuit 34 among the stored seed coefficient data. The tap coefficient is generated from the seed coefficient data (the seed coefficient data of the class represented by the class code supplied from the class code generation circuit 34) and the parameter, and the generated tap coefficient is supplied to the prediction calculation circuit 35 ( Output.

  FIG. 40 shows a configuration example of a coefficient generation circuit 321 that generates tap coefficients for each class from seed coefficient data and parameters.

  The coefficient generation circuit 321 includes a storage unit 331, a selection switch 332, a coefficient generation circuit 333, and a remote control radio wave reception circuit 335.

  The class code output from the class code generation circuit 34 (FIG. 39) is supplied to the ROM tables 341 to 343 of the storage unit 331. The storage unit 331 stores a ROM table of seed coefficient data for each class obtained by learning described later for each parameter type. That is, a ROM table of different seed coefficient data is provided for each parameter value range. In FIG. 40, the storage unit 331 includes a ROM table 341 of a seed coefficient data set A, a ROM table 342 of a seed coefficient data set B, and a ROM table 343 of a seed coefficient data set C. Although the parameter types are divided into three types, the parameter value ranges can be further classified into other types than the three types.

  The selection switch 332 selects one of the outputs (seed coefficient data) of the ROM tables 341 to 343 based on the parameters supplied from the remote control radio wave receiving circuit 335, and sends the selected seed coefficient data to the coefficient generation circuit 333. Supply.

  The coefficient generation circuit 333 generates tap coefficients corresponding to the class code supplied from the class code generation circuit 34 based on the seed coefficient data supplied from the selection switch 332 and the parameters supplied from the remote control radio wave reception circuit 335. It is generated and supplied (output) to the prediction calculation circuit 35.

  The remote control radio wave reception circuit 335 receives the parameter transmitted from the remote control 4 and supplies the received parameter to the selection switch 332 and the coefficient generation circuit 333. Further, the remote control radio wave reception circuit 335 stores the parameter received from the remote control 4 immediately before and supplies it to the coefficient generation circuit 333 as necessary.

  Here, it is assumed that the remote controller 4 includes, for example, an operation knob operated by the user, and transmits a parameter having a value corresponding to the operation to the remote control radio wave receiving circuit 335. This parameter corresponds to the resolution of an image composed of pixel values obtained by the prediction calculation circuit 35.

  In the coefficient generation circuit 321 in FIG. 40, seed coefficient data selected from outputs (seed coefficient data) of the ROM tables 341 to 343 according to the operation of the remote controller 4 by the user, and further in the coefficient generation circuit 333 The generated tap coefficient changes. Therefore, it can be said that the tap coefficient supplied to the prediction calculation circuit 35 (FIG. 38) is an optimization coefficient because it is the optimum tap coefficient for the parameter set by being operated by the user.

  Next, image conversion processing performed by the image signal processing circuit 173 and the coefficient generation circuit 321 in FIG. 39 will be described.

  In the image conversion process according to the first embodiment described with reference to FIG. 10, in step S <b> 24, the coefficient generation circuit 15 taps stored at an address corresponding to the class code supplied from the class code generation circuit 34. As a coefficient, the tap coefficient output by the ROM table selected by the ROM table selection process of FIG. 11 is supplied (output) to the prediction arithmetic circuit 35.

  On the other hand, in the image conversion process according to the eighth embodiment, the coefficient generation circuit 333 of the coefficient generation circuit 321 supplies the selection switch 332 from the ROM table selection process described later with reference to FIG. The tap coefficient is generated based on the seed coefficient data and the parameter supplied from the remote control radio wave receiving circuit 335. Further, the coefficient generation circuit 321 supplies (outputs) the generated tap coefficient to the prediction calculation circuit 35 as the tap coefficient stored at the address corresponding to the class code supplied from the class code generation circuit 34.

  Other processes in the image conversion process of the eighth embodiment are performed in the same manner as the image conversion process of FIG.

  Next, the ROM table selection process in the eighth embodiment will be described with reference to the flowchart in FIG.

  First, in step S121, the remote control radio wave reception circuit 335 of the coefficient generation circuit 321 determines whether or not an operation command has been received from the remote control 4. If it is determined in step S121 that an operation command has not been received from the remote controller 4, the process proceeds to step S122, and the selection switch 332 selects the previous (previously selected) output from the ROM tables 341 to 343 of the storage unit 331. Select the output of the ROM table. After step S122, the process proceeds to step S125.

  On the other hand, if it is determined in step S121 that an operation command has been received from the remote controller 4, the process proceeds to step S123, and the remote control radio wave reception circuit 335 determines whether or not the operation command is a command representing a parameter.

  If it is determined in step S123 that the received operation command is not a command representing a parameter, the process proceeds to step S122, and as described above, the selection switch 332 includes the outputs from the ROM tables 341 to 343 of the storage unit 331. Select the output of the previous ROM table.

  On the other hand, if it is determined in step S123 that the received operation command is a command representing a parameter, the process proceeds to step S124, and the remote control radio wave receiving circuit 335 supplies the received parameter to the selection switch 332. Then, the selection switch 332 selects the output (seed coefficient data) of the ROM table corresponding to the parameter from the outputs of the ROM tables 341 to 343, supplies it to the coefficient generation circuit 333, and proceeds to step S125.

  In step S125, the coefficient generation circuit 333 generates a tap coefficient based on the seed coefficient data supplied from the selection switch 332 and the parameter supplied from the remote control radio wave reception circuit 335, and supplies the tap coefficient to the prediction calculation circuit 35 ( Output), and the process returns to step S121. If no parameter is transmitted from the remote control 4 to the remote control radio wave reception circuit 335, the remote control radio wave reception circuit 335 stores the parameter received from the remote control 4 immediately before and stored in the coefficient generation circuit 333. Can be supplied.

  This ROM table selection process is executed in parallel with the image conversion process until the above-described image conversion process is completed, that is, until it is determined that the input image signal is completed.

  Next, generation of tap coefficients in the coefficient generation circuit 333 and learning of seed coefficient data stored in the ROM tables 341 to 343 of the storage unit 331 will be described.

  Now, the high-quality image signal (high-quality image signal) is used as the second image signal, and the high-quality image signal is filtered by LPF (Low Pass Filter) to reduce the image quality (resolution). Using a low-quality image signal (low-quality image signal) as a first image signal, extracting a prediction tap from the low-quality image signal, and using the prediction tap and the tap coefficient, the pixel value of the high-quality pixel is, for example, Consider obtaining (predicting) by linear primary prediction calculation of equation (1).

  Here, the pixel value y of the high-quality pixel can be obtained not by the linear primary expression shown in Expression (1) but by a higher-order expression of the second or higher order.

On the other hand, the coefficient generation circuit 321, the tap coefficient w _n is the seed coefficient data stored in the ROM table 341 to 343 of the storage unit 331, but is generated from the parameters supplied from the remote control radio wave receiving circuit 335, the The generation of the tap coefficient w _n in the coefficient generation circuit 321 is performed using, for example, the following equation using seed coefficient data and parameters.

・・・（９）

... (9)

However, in the equation (9), beta _{m, n} represents the m-th species coefficient data used for determining the n-th tap coefficient w _n, z represents a parameter. In equation (9), the tap coefficient w _n is obtained using M seed coefficient data β _{1, n} , β _{2, n} ,..., Β _{M, n} .

Here, the formula for obtaining the tap coefficient w _n from the seed coefficient data β _{m, n} and the parameter z is not limited to the formula (9).

Now, a value z ^m−1 determined by the parameter z in equation (9) is defined by the following equation by introducing a new variable t _m .

・・・（１０）

(10)

  By substituting equation (10) into equation (9), the following equation is obtained.

・・・（１１）

(11)

According to the equation (11), the tap coefficient w _n is obtained by a linear linear expression of the seed coefficient data β _{m, n} and the variable t _m .

Now, when the true value of the pixel value of the high-quality pixel of the k-th sample is expressed as y _k and the predicted value of the true value y _k obtained by the equation (1) is expressed as y _k ′, the prediction error e _k is expressed by the following equation.

・・・（１２）

(12)

Now, since the predicted value y _k ′ of Expression (12) is obtained according to Expression (1), when y _k ′ of Expression (12) is replaced according to Expression (1), the following expression is obtained.

・・・（１３）

(13)

In Equation (13), x _{n, k} represents the n-th low-quality pixel that constitutes the prediction tap for the high-quality pixel of the k-th sample.

To w _n of formula (13), by substituting equation (11), the following equation is obtained.

・・・（１４）

(14)

Prediction error e _k 0 to seed coefficient data beta _{m, n} of formula (14), is the optimal for predicting the high-quality pixel, for all the high-quality pixel, such species coefficient data It is generally difficult to obtain β _{m, n} .

Therefore, as a standard indicating that the seed coefficient data β _{m, n} is optimal, for example, when the least square method is adopted, the optimal seed coefficient data β _{m, n} is expressed by the following equation. It can be obtained by minimizing the sum E of square errors.

・・・（１５）

(15)

However, in Expression (15), K is a high-quality pixel y _k and low-quality pixels x _{1, k} , x _{2, k} ,..., X _N that constitute a prediction tap for the high-quality pixel y _{k. , k} represents the number of samples (the number of learning samples).

The minimum value (minimum value) of the sum E of square errors in equation (15) is β _{m, where} 0 is a partial differentiation of the sum E with seed coefficient data β _{m, n} , as shown in equation (16) _. given by _n .

・・・（１６）

... (16)

  By substituting equation (13) into equation (16), the following equation is obtained.

・・・（１７）

... (17)

Now, X _{i, p, j, q} and Y _{i, p} are defined as shown in equations (18) and (19).

・・・（１８）

... (18)

・・・（１９）

... (19)

In this case, Expression (17) can be expressed by a normal equation shown in Expression (20) using X _{i, p, j, q} and Y _{i, p} .

・・・（２０）

... (20)

The normal equation of Expression (20) can be solved for the seed coefficient data β _{m, n} by using, for example, a sweeping method (Gauss-Jordan elimination method) or the like.

In the ROM table 341 to 343 of the storage unit 331 of FIG. 40, a number of high-quality pixel y _1, y _2, · · ·, as well as the teacher data serving as a teacher of learning y _K, the high-quality pixel y _k The low-quality pixels x _{1, k} , x _{2, k} ,..., X _{N, k} that constitute the prediction tap for, are obtained by performing learning to solve equation (20) as student data to be learning students. The seed coefficient data β _{m, n} is stored for each range of the parameter z, and the coefficient generation circuit 333 of the coefficient generation circuit 321 supplies the seed coefficient data β _{m, n} and the remote control radio wave reception circuit 335. From the parameter z, the tap coefficient w _n is generated according to the equation (9). Then, in the prediction calculation circuit 35 of FIG. 39, the formula (1) is calculated using the tap coefficient w _n and the low image quality pixel x _n constituting the prediction tap for the target pixel as the high image quality pixel. Thus, the pixel value of the pixel of interest as the high-quality pixel (predicted value close to it) is obtained.

FIG. 42 shows a configuration example of a learning device that performs learning for obtaining seed coefficient data β _{m, n} by building and solving the normal equation of Expression (20). In the figure, portions corresponding to those in FIG. 5 are denoted by the same reference numerals, and description thereof will be omitted as appropriate.

A learning image signal used for learning the seed coefficient data β _{m, n} is input to the learning device. Here, as the learning image signal, for example, a high-resolution image signal with high resolution can be used.

  In the learning apparatus, the learning image signal is supplied to the teacher data generation unit 51 and the student data generation unit 53.

  The teacher data generation unit 51 generates teacher data from the learning image signal supplied thereto and supplies it to the teacher data storage unit 52. That is, here, the teacher data generation unit 51 supplies the high-quality image signal as the learning image signal as it is to the teacher data storage unit 52 as teacher data.

  The teacher data storage unit 52 stores a high-quality image signal as teacher data supplied from the teacher data generation unit 51.

  The student data generation unit 53 generates student data from the learning image signal and supplies it to the student data storage unit 54. In other words, the student data generation unit 53 generates a low-quality image signal by filtering the high-quality image signal as the learning image signal, thereby reducing the resolution. To the student data storage unit 54.

  Here, in addition to the learning image signal, the student data generation unit 53 is supplied from the parameter generation unit 351 with some values in the range that the parameter z can take. That is, now, assuming that the value that the parameter z can take is a real number in the range of 0 to Z, the student data generation unit 53 has, for example, z = 0, 1, 2,. It is supplied from the section 351.

  The student data generation unit 53 generates a low-quality image signal as student data by filtering the high-quality image signal as the learning image signal with an LPF having a cutoff frequency corresponding to the parameter z supplied thereto. To do.

  Therefore, in this case, as shown in FIG. 43, the student data generation unit 53 generates Z + 1 types of low-quality image signals as student data having different resolutions for the high-quality image signal as the learning image signal. .

  Here, for example, as the value of the parameter z increases, the high-quality image signal is filtered using an LPF having a higher cutoff frequency, and a low-quality image signal as student data is generated. So here. The lower the image quality signal corresponding to the larger parameter z, the lower the resolution.

  In the present embodiment, in order to simplify the explanation, the student data generation unit 53 reduces the resolution in both the horizontal direction and the vertical direction of the high-quality image signal by an amount corresponding to the parameter z. Assume that an image quality image signal is generated.

  Returning to FIG. 42, the student data storage unit 54 stores the student data supplied from the student data generation unit 53.

  The prediction tap extraction unit 55 sequentially sets pixels constituting the high-quality image signal as the teacher data stored in the teacher data storage unit 52 as the attention teacher pixels, and stores the attention teacher pixels in the student data storage unit 54. A prediction tap having the same tap structure as that formed by the prediction tap extraction circuit 31 of FIG. 39 is formed by extracting predetermined ones of low-quality pixels constituting the low-quality image signal as the student data. And supplied to the adding portion 352.

  The class tap extraction unit 56 extracts a predetermined one of the low-quality pixels constituting the low-quality image signal as the student data stored in the student data storage unit 54 from the teacher pixel of interest, as shown in FIG. A class tap having the same tap structure as that formed by the class tap extraction circuit 33 is configured and supplied to the class code generation unit 57.

  Note that the parameter z generated by the parameter generation unit 351 is supplied to the prediction tap extraction unit 55 and the class tap extraction unit 56, and the prediction tap extraction unit 55 and the class tap extraction unit 56 perform parameter generation. Using the student data generated in accordance with the parameter z supplied from the unit 351 (here, the low-quality image signal as the student data generated using the LPF having the cutoff frequency corresponding to the parameter z) Each of the prediction tap and the class tap is configured.

  The class code generation unit 57 performs the same class classification as the class code generation circuit 34 of FIG. 39 based on the class tap output from the class tap extraction unit 56, and adds the class code corresponding to the resulting class. To the unit 352.

  The parameter generation unit 351 generates, for example, z = 0, 1, 2,..., Z as described above as several values in the range that the parameter z can take, and supplies the generated values to the student data generation unit 53. To do. The parameter generation unit 351 also supplies the generated parameter z to the prediction tap extraction unit 55, the class tap extraction unit 56, and the addition unit 352.

  The adding unit 352 reads the attention teacher pixel from the teacher data storage unit 52, and the student data that configures the attention teacher pixel, the prediction tap configured for the attention teacher pixel supplied from the prediction tap extraction unit 55, and the The addition for the parameter z when the student data is generated is performed for each class code supplied from the class code generator 57.

That is, the addition unit 352 includes the teacher data y _k stored in the teacher data storage unit 52, the prediction tap x _{i, k} (x _{j, k} ) output from the prediction tap extraction unit 55, and the class code generation unit 57. In addition to the class code output by, the parameter z when the student data used to configure the prediction tap is generated is also supplied from the parameter generation unit 351.

Then, the adding unit 352 uses the prediction tap (student data) x _{i, k} (x _{j, k} ) and the parameter z for each class corresponding to the class code supplied from the class code generating unit 57, and uses the formula ( 20) Multiplication (x _{i, k} t _p x _{j, k} t _q ) of the student data and the parameter z for obtaining the component X _{i, p, j, q} defined by the equation (18) in the matrix on the left side of 20) And an operation corresponding to summation (Σ). Incidentally, t _p of formula (18), according to equation (10), is calculated from the parameter z. The same applies to _{tq in} equation (18).

Furthermore, the adding unit 352 uses the prediction tap (student data) x _{i, k} , the teacher data y _k , and the parameter z for each class corresponding to the class code supplied from the class code generating unit 57, Multiplication (x _{i, k} t) of student data x _{i, k} , teacher data y _k , and parameter z for obtaining the component Y _{i, p} defined by equation (19) in the vector on the right side of equation (20) _p y _k ) and a calculation corresponding to summation (Σ). Incidentally, t _p of formula (19), according to equation (10), is calculated from the parameter z.

In other words, the adding unit 352 performs the left-side matrix component X _{i, p, j, q} and the right-side vector component Y _{i, p} is stored in its built-in memory (not shown), and the matrix component X _{i, p, j, q} or vector component Y _{i, p is} newly selected as a teacher pixel of interest. For the teacher data, the corresponding component x _{i, k} t _p x _{j, k} t _q or x calculated using the teacher data y _k , student data x _{i, k} (x _{j, k} ) and parameter z _{i, k} t _p y _k is added (addition represented by summation in component X _{i, p, j, q in} equation (18) or component Y _{i, p} in equation (19) is performed).

  Then, the addition unit 352 performs the above-described addition for all the parameters z of the values 0, 1,..., Z using all the teacher data stored in the teacher data storage unit 52 as the target teacher pixel. Thus, when the normal equation shown in the equation (20) is established for each class, the normal equation is supplied to the seed coefficient calculation unit 353.

The seed coefficient calculation unit 353 obtains and outputs the seed coefficient data β _{m, n} for each class by solving the normal equation for each class supplied from the addition unit 352.

  Next, processing (learning processing) of the learning device in FIG. 42 will be described with reference to the flowchart in FIG.

  First, in step S131, the teacher data generation unit 51 and the student data generation unit 53 respectively generate and output teacher data and student data from the learning image signal. That is, the teacher data generation unit 51 outputs the learning image signal as it is as teacher data. Further, the student data generation unit 31 is supplied with the parameter z of Z + 1 values generated by the parameter generation unit 351, and the student data generation unit 31 receives the Z + 1 pieces of learning image signals from the parameter generation unit 351. Z + 1 frame student data is generated for the teacher data (learning image signal) of each frame by filtering with the LPF of the cutoff frequency corresponding to the parameter z of the value (0, 1,..., Z). Output.

  The teacher data output from the teacher data generation unit 51 is supplied to and stored in the teacher data storage unit 52, and the student data output from the student data generation unit 53 is supplied to and stored in the student data storage unit.

  Thereafter, the process proceeds to step S132, the parameter generation unit 351 sets the parameter z to, for example, 0 as an initial value, and supplies the parameter z to the prediction tap extraction unit 55, the class tap extraction unit 56, and the addition unit 352, The process proceeds to step S133. In step S <b> 133, the prediction tap extraction unit 55 sets the teacher data stored in the teacher data storage unit 52 as notable teacher pixels that have not yet been identified as the notable teacher pixels. Furthermore, in step S133, the prediction tap extraction unit 55 stores the student data for the parameter z output from the parameter generation unit 351, which is stored in the student data storage unit 54 with respect to the teacher pixel of interest (teacher data serving as the teacher data of interest). (Study data generated by filtering the learning image signal corresponding to the parameter z with the LPF of the cutoff frequency corresponding to the parameter z) is configured (extracted), supplied to the adding unit 352, and the class The tap extraction unit 56 also configures (extracts) class taps from the student data for the parameter z output from the parameter generation unit 351 and stored in the student data storage unit 54 for the teacher pixel of interest, and the class code generation unit 57 To supply.

  Then, the process proceeds to step S134, where the class code generation unit 57 classifies the target teacher pixel in the same manner as in the class code generation circuit 34 in FIG. 39, based on the class tap for the target teacher pixel, and the result. The class code corresponding to the obtained class is output to the adding unit 352, and the process proceeds to step S135.

In step S135, the adding unit 352 reads the target teacher pixel from the teacher data storage unit 52, uses the target teacher pixel, the prediction tap supplied from the prediction tap extraction unit 55, and the parameter z output from the parameter generation unit 351. , The left side matrix component x _{i, k} t _{p xj, k} t _q in equation (20) and the right side vector component x _{i, k} t _p y _k are calculated. Further, the addition unit 352 applies the matrix corresponding to the class code from the class code generation unit 57 among the already obtained matrix components and vector components from the target pixel, the prediction tap, and the parameter z. components x _i of the obtained _{matrix, k t p x j, k} t q and the vector components x _{i of} summing the k t _p y _k, the process proceeds to the step S136.

  In step S136, the parameter generation unit 351 determines whether or not the parameter z output by itself is equal to Z which is the maximum value that can be taken. In step S136, when it is determined that the parameter z output from the parameter generation unit 351 is not equal to the maximum value Z (less than the maximum value Z), the process proceeds to step S137, and the parameter generation unit 351 sets the parameter z to the parameter z. 1 is added, and the added value is output as a new parameter z to the prediction tap extraction unit 55, the class tap extraction unit 56, and the addition unit 352. Then, the process returns to step S133, and the same processing is repeated thereafter.

  If it is determined in step S136 that the parameter z is equal to the maximum value Z, the process proceeds to step S138, and the prediction tap extraction unit 55 stores teacher data that has not yet been set as the target teacher pixel in the teacher data storage unit 52. Determine whether it has been. If it is determined in step S138 that the teacher data that is not the attention teacher pixel is still stored in the teacher data storage unit 52, the prediction tap extraction unit 55 newly sets the teacher data that is not yet the attention teacher pixel. Returning to step S132 as the teacher pixel of interest, the same processing is repeated thereafter.

  If it is determined in step S138 that the teacher data that is not the focused teacher pixel is not stored in the teacher data storage unit 52, the adding unit 352 determines the formula ( The matrix on the left side and the vector on the right side in 20) are supplied to the seed coefficient calculation unit 353, and the process proceeds to step S139.

In step S139, the seed coefficient calculation unit 353 solves the normal equation for each class configured by the matrix on the left side and the vector on the right side in the equation (20) for each class supplied from the addition unit 352, thereby classifying each class. Then, the seed coefficient data β _{m, n} is obtained and output, and the process is terminated.

  In addition, due to the insufficient number of learning image signals, etc., there may occur classes in which the number of normal equations necessary for obtaining seed coefficient data cannot be obtained. The seed coefficient calculating unit 353 outputs, for example, preset seed coefficient data.

In the ROM tables 341 to 343 of the storage unit 331 in FIG. 40, the seed coefficient data β _{m, n} for each class obtained as described above is stored.

  In the above-described case, the learning image signal is used as teacher data corresponding to the second image signal as it is, and the low-quality image signal in which the resolution of the learning image signal is degraded is used as the first image signal. Since the seed coefficient data is learned as the corresponding student data, the seed coefficient data is a resolution improvement process for converting the first image signal into the second image signal whose resolution is improved. What performs the image conversion process of this can be obtained.

  In this case, the image signal processing circuit 173 can improve the horizontal resolution and vertical resolution of the image signal corresponding to the parameter z. Therefore, in this case, it can be said that the parameter z is a parameter corresponding to the resolution.

  Here, depending on the selection method of the student data corresponding to the first image signal and the image signal to be the teacher data corresponding to the second image signal, the seed coefficient data is to be subjected to various image conversion processes. Obtainable.

  That is, for example, a high-quality image signal is used as teacher data, and learning processing is performed using, as student data, an image signal in which noise of a level corresponding to the parameter z is superimposed on the high-quality image signal as the teacher data. As a result, the seed coefficient data may be obtained by performing image conversion processing as noise removal processing for converting the first image signal into the second image signal from which the noise contained therein is removed (reduced). it can.

  When the seed coefficient data for noise removal processing is stored in the ROM tables 341 to 343 of the storage unit 331, the image signal processing circuit 173 can perform noise removal of the image signal corresponding to the parameter z. .

Incidentally, in the above case, defines the tap coefficient w _n, in as shown in Equation _{(9), β 1, n} z 0 + β 2, n z 1 + ··· + β M, n z M-1 and, by the equation (9), the horizontal and vertical resolution, either, was to obtain the tap coefficient w _n for improving corresponding to the parameter z, as the tap coefficient w _n, horizontal resolution It is also possible to obtain a resolution that independently improves the vertical resolution corresponding to the independent parameters z _x and z _y .

That is, the tap coefficients w _n, instead of the equation (9), for example, cubic polynomial ^{_{β 1, n z x 0 z}} y 0 + β 2, n z x 1 z y 0 + β 3, n z x 2 z y ⁰ + β _{4, n} z _x ³ z _y ⁰ + β _{5, n} z _x ⁰ z _y ¹ + β _{6, n} z _x ⁰ z _y ² + β _{7, n} z _x ⁰ z _y ³ + β _{8, n} z _x ¹ z _y ¹ + β _{9, n} z _x ² z _y ¹ + β _{10, n} z _x ¹ z _y ² , and variable t _m defined in equation (10) is replaced with equation (10), t ₁ = z _x ⁰ z _y ⁰ , t ₂ = z _x ¹ z _y ⁰ , t ₃ = z _x ² z _y ⁰ , t ₄ = z _x ³ z _y ⁰ , t ₅ = z _x ⁰ z _y ¹ , t ₆ = z _x ⁰ z _y ² , t ₇ = z _x ⁰ z _y ³ , t ₈ = z _x ¹ z _y ¹ , t ₉ = z _x ² z _y ¹ , t ₁₀ = z _x ¹ z _y ² . Again, the tap coefficient w _n is finally can be represented by the formula (11), therefore, in the learning apparatus (Fig. 42), corresponding to the parameter z _x and z _y, horizontal teacher data The image signal with degraded resolution and vertical resolution is used as the student data, and learning is performed to obtain the seed coefficient data β _{m, n} , so that the horizontal resolution and the vertical resolution can be set as independent parameters z _x and z _y. in response to, it can be obtained tap coefficients w _n to improve independently.

In addition, for example, in addition to the parameters z _x and z _y corresponding to the horizontal resolution and the vertical resolution, respectively, by introducing a parameter z _t corresponding to the resolution in the time direction, the horizontal resolution, the vertical resolution, and the time resolution are independent parameters z _x, z _y, corresponding to the z _t, it is possible to determine the tap coefficient w _n to improve independently.

  FIG. 45 is a diagram for explaining parameter values received by the remote control receiving circuit 335 in the coefficient generation circuit 321 of FIG. 39 and a ROM table selected based on the values.

  The upper side of FIG. 45 shows a selection switch when the remote controller 4 transmits, for example, one parameter z indicating the resolution in both the horizontal direction and the vertical direction of the high-quality image signal to the remote control radio wave receiving circuit 335 as described above. It is a figure explaining the ROM table which 332 selects.

In each of the ROM tables 341 to 343, seed coefficient data sets A and B respectively obtained by learning while changing the parameter z in the range of 0 to z _a , z _{a to} z _b , z _{b to} z _c. , C are stored.

In this case, for example, when the remote control radio wave reception circuit 335 supplies a parameter z of 0 or more and less than z _a to the selection switch 332, the selection switch 332 outputs the output (seed coefficient data) of the ROM table 341 of the seed coefficient data set A. select. Further, when the remote control radio wave receiving circuit 335 supplies the parameter z of less than z _a higher z _b to the selection switch 332, the selection switch 332 selects the output of the ROM table 342 of the set of species coefficient data B (seed coefficient data) . Furthermore, the remote control radio wave receiving circuit 335 is supplied to the selection switch 332 a z _b or Z following parameters z, selection switch 332 selects the output of the ROM table 343 of the set C of the seed coefficient data (seed coefficient data).

Figure 45 lower, when the remote controller 4 is, for example, to transmit as described above, two parameters z _x and z _y independent, each representing a horizontal and vertical resolution of the high-quality image signal to the remote control radio receiver circuit 335 It is a figure explaining the ROM table which the selection switch 332 selects.

In the ROM table 341, a set A of seed coefficient data obtained by learning while changing the parameter z _x in the range of 0 to z _x1 and changing the parameter z _y in the range of 0 to z _y1. Is remembered.

In the ROM table 342, a set B of seed coefficient data respectively obtained by performing learning while changing the parameter z _x in the range of z _{x1 to} Zx and changing the parameter z _y in the range of 0 to z _y1. Is remembered.

In the ROM table 343, seed coefficient data sets respectively obtained by learning while changing the parameter z _x in the range of 0 to z _x1 Zx and changing the parameter z _y in the range of z _{y1 to} Zy. C is stored.

In this case, for example, a remote control radio wave receiving circuit 335, and zero or more z _x1 less parameters z _x, is supplied to the selection switch 332 a parameter z _y from 0 to less than z _y1, selection switch 332, a set of seed coefficient data The output (seed coefficient data) of the A ROM table 341 is selected. When the remote control radio wave receiving circuit 335 supplies the parameter z _{x not} less than z _{x1 and not} more than Zx and the parameter z _{y not} less than 0 and less than z _y1 to the selection switch 332, the selection switch 332 reads the ROM of the set B of seed coefficient data. The output (seed coefficient data) of the table 341 is selected. Furthermore, the remote control radio wave receiving circuit 335, and zero or more z _x1 less parameters z _x, Supplying z _y1 or Zy following parameters z _y to the selection switch 332, the selection switch 332, the set C of the seed coefficient data ROM The output (seed coefficient data) of the table 341 is selected. The ROM table storing the seed coefficient data by performing learning for obtaining the seed coefficient data for a range where the parameter z _x is not less than z _{x1 and not} more than Zx and the parameter z _y is not less than z _{y1 and not} more than Zy is stored in the storage unit. 331 can be stored.

  As described above, in the eighth embodiment, the coefficient generation circuit 321 receives the parameter transmitted from the remote controller 4 when the user operates the remote controller 4, and based on the parameter, the optimum seed coefficient data Is selected to generate a tap coefficient, which is output (supplied) to the image signal processing circuit 173. Then, the image signal processing circuit 173 obtains and outputs, for example, a high-quality image from the input image signal using the supplied optimum tap coefficient, so that an image conversion process optimum for the parameter can be performed. For example, as described above, this parameter can be a parameter relating to image resolution or noise removal. Therefore, the user operates the remote controller 4 so that the image displayed on the CRT 16 is an image having a desired image quality. It can be.

  Therefore, it is possible to perform optimal image conversion processing by utilizing (utilizing) the user's viewing characteristics (preference).

  In the embodiment described above, the bay 3 can be attached to and detached from the television 1 and the bay 3 can be upgraded regardless of the main body of the television 1, so that the flexibility and flexibility of image conversion processing in the television 1 can be increased. Can be improved. Moreover, since part of the image conversion processing is performed in the bay 3, the burden of processing on the main body of the television 1 can be reduced.

  In the above-described embodiment, the coefficient generation circuit 15 is disposed in the bay 3 and is detachable. However, the coefficient generation circuit 15 may be disposed in the bay 3 including the image signal processing circuit 173.

  For example, the coefficient generation circuit 15 in the bay 3 receives an operation command transmitted from the remote controller 4 and selects an optimal ROM table according to the operation command. Can view a high-resolution image without being conscious of the fact that the image conversion process is being performed.

  In the above-described example, the case where the present invention is applied to one television 1 has been described. However, the present invention arranges a plurality of televisions 1 in a grid pattern, and each screen of each of the plurality of televisions 1 is displayed. The present invention can also be applied to a multi-television system that displays images on a single screen.

  The above-described image conversion process, ROM table selection process, and other series of processes can be executed by dedicated hardware or can be executed by software. When a series of processing is performed by software, for example, the series of processing can be realized by causing a computer as shown in FIG. 46 to execute a program.

  46, a CPU (Central Processing Unit) 401 executes various processes according to a program stored in a ROM (Read Only Memory) 402 or a program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. To do. The RAM 403 appropriately stores data necessary for the CPU 401 to execute various processes.

  The CPU 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input / output interface 405 is also connected to the bus 404.

  The input / output interface 405 includes an input unit 406 including a keyboard and a mouse, a display including a CRT (Cathode Ray Tube) and an LCD (Liquid Crystal display), an output unit 407 including a speaker, and a hard disk. A communication unit 409 including a storage unit 408, a modem, a terminal adapter, and the like is connected. The communication unit 409 performs communication processing via a network such as the Internet.

  A drive 410 is connected to the input / output interface 405 as necessary, and a magnetic disk 421, an optical disk 422, a magneto-optical disk 423, a semiconductor memory 424, or the like is appropriately mounted, and a computer program read from these is loaded. It is installed in the storage unit 408 as necessary.

  In the present specification, the steps described in the flowcharts are executed in parallel or individually even if they are not necessarily processed in time series, as well as processes performed in time series in the described order. It also includes processing.

1 is a perspective view showing an embodiment of a television receiver 1 to which the present invention is applied. It is a block diagram which shows the structural example of 1st Embodiment of the television 1 of FIG. 2 is a block diagram illustrating a configuration example of an image signal processing circuit 14 and a coefficient generation circuit 15. FIG. It is a figure which shows a prediction tap and a class tap. It is a block diagram which shows the structural example of the learning apparatus which learns a tap coefficient. It is a flowchart explaining the learning process which learns a tap coefficient. It is a flowchart explaining an image conversion process. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 15. FIG. It is a figure which shows the example of the image utilized for the calculation of noise intensity. It is a flowchart explaining an image conversion process. It is a flowchart explaining the ROM table selection process of 1st Embodiment. It is a block diagram which shows the structural example of 2nd Embodiment of the television 1 of FIG. 2 is a block diagram illustrating a configuration example of an image signal processing circuit 14 and a coefficient generation circuit 101. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 101. FIG. It is a flowchart explaining the ROM table selection process of 2nd Embodiment. It is a block diagram which shows the structural example of 3rd Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 141 and a coefficient generation circuit 142. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 142. FIG. It is a flowchart explaining the ROM table selection process of 3rd Embodiment. It is a block diagram which shows the structural example of 4th Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 173 and a coefficient generation circuit 174. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 174. FIG. It is a flowchart explaining the ROM table selection process of 4th Embodiment. It is a block diagram which shows the structural example of 5th Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 14 and a coefficient generation circuit 211. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 211. FIG. 3 is a block diagram illustrating a configuration example of a learning circuit 223. FIG. It is a flowchart explaining the ROM table selection process of 5th Embodiment. It is a block diagram which shows the structural example of 6th Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 173 and a coefficient generation circuit 255. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 255. FIG. It is a flowchart explaining the ROM table selection process of 6th Embodiment. It is a block diagram which shows the structural example of 7th Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 173 and a coefficient generation circuit 283. FIG. 3 is a block diagram illustrating a detailed configuration example of a coefficient generation circuit 283. FIG. It is a flowchart explaining the ROM table selection process of 7th Embodiment. It is a flowchart explaining the tap coefficient update process of 7th Embodiment. It is a block diagram which shows the structural example of 8th Embodiment of the television 1 of FIG. 3 is a block diagram illustrating a configuration example of an image signal processing circuit 173 and a coefficient generation circuit 321. FIG. 3 is a block diagram illustrating a configuration example of a coefficient generation circuit 321. FIG. It is a flowchart explaining the ROM table selection process of 8th Embodiment. It is a block diagram which shows the structural example of the learning apparatus which learns seed coefficient data. It is a figure for demonstrating learning of seed coefficient data. It is a flowchart explaining the learning process which learns seed coefficient data. It is a figure for demonstrating learning of seed coefficient data. It is a block diagram which shows the structural example of one Embodiment of the computer to which this invention is applied.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Television receiver, 2 slots, 3 bays, 4 Remote control, 11 Image signal input part, 12 Antenna, 13 Tuner, 14 Image signal processing circuit, 15 Coefficient generation circuit, 16 CRT, 17 Remote control radio wave reception circuit, 18 Control circuit , 31 prediction tap extraction circuit, 32 class classification unit, 33 class tap extraction circuit, 34 class code generation circuit, 35 prediction calculation circuit, 71 storage unit, 72 selection switch, 73 remote control radio wave reception circuit, 74 reception noise detection circuit, 81 To 84 ROM table, 85 noise intensity calculation circuit, 86, 87 memory, 101 coefficient generation circuit, 111 storage unit, 112 selection switch, 113 channel frequency detection unit, 114 remote control power Receiving circuit, 121 to 124 ROM table, 125 channel frequency counting circuit, 126 memory, 141 image signal processing circuit, 142 counting generation circuit, 143 resizing circuit, 151 storage unit, 152 selection switch, 153 remote control radio wave receiving circuit, 161 to 164 ROM table, 171 image signal input unit, 172 input terminal, 173 image signal processing circuit, 174 coefficient number generation circuit, 181 DVD device, 191 storage unit, 192 selection switch, 193 playback speed frequency detection unit, 194 remote control radio wave reception circuit, 201 to 203 ROM table, 211 coefficient generation circuit, 221 storage unit, 222 selection switch, 223 learning circuit, 224 memory, 225 local Noise detection unit, 231 to 234 ROM table, 235 local noise detection circuit, 236 memory, 250 image signal input unit, 251 to 253 input terminal, 254 input selection switch, 255 coefficient generation circuit, 256, 257 VTR device, 261 storage unit , 262 selection switch, 263 image source detection unit, 264 remote control radio wave reception circuit, 271 to 273 ROM table, 281 image signal input unit, 282 image signal output unit, 283 coefficient generation circuit, 291 output terminal, 303 learning circuit, 304 remote control Radio wave reception circuit, 321 coefficient generation circuit, 331 storage unit, 332 selection switch, 333 coefficient generation circuit, 335 remote control radio wave reception circuit, 341 to 343 R M table

Claims (16)

In an image signal processing apparatus for processing an image signal,
First command receiving means for receiving an operation command from the outside;
Execution means for executing processing according to the operation command received by the first command receiving means;
Image signal processing means for processing the image signal;
Using means used for processing in the image signal processing means,
The utilization means is composed of a semiconductor chip and is detachable from the image signal processing device.
Second command receiving means for receiving the same operation command as the operation command received by the first command receiving means;
An image signal processing apparatus comprising at least control means for controlling processing in the image signal processing means based on the operation command received by the second command receiving means. The image signal processing apparatus according to claim 1, wherein the first and second command receiving means receive the operation command transmitted wirelessly from a remote control device. The control means includes a prediction coefficient storage means for storing a prediction coefficient for each predetermined class obtained in advance by learning, which is used to convert the first image signal into the second image signal. ,
The image signal processing means includes
Class classification means for classifying the second image signal into any one of a plurality of classes;
The calculation means for obtaining the second image signal by calculation using the prediction coefficient of the class of the second image signal and the first image signal. Image signal processing apparatus. The prediction coefficient storage means stores a plurality of sets of prediction coefficients obtained by learning using different types of images,
The control means selects any one of the plurality of sets of prediction coefficients stored in the prediction coefficient storage means based on the operation command received by the second command receiving means. The image signal processing apparatus according to claim 3 , wherein the processing in the image signal processing unit is controlled by supplying the calculation unit to the calculation unit. A television signal receiving means for receiving a television signal;
Channel selection means for selecting an image signal of a predetermined channel from the television signal;
The execution means executes processing for causing the channel selection means to select an image signal of a predetermined channel based on the operation command received by the first command reception means,
5. The image signal processing apparatus according to claim 4 , wherein the image signal processing means obtains the second image signal by using the image signal selected by the channel selection means as the first image signal. . The utilization means is:
Channel selection frequency counting means for counting the channel selection frequency at which the channel of the television signal is selected based on the operation command received by the second command receiving means;
The image signal processing apparatus according to claim 5 , further comprising channel selection frequency storage means for storing the channel selection frequency. The control unit determines a frequency band of a channel based on the operation command received by the second command receiving unit, and the plurality of sets stored in the prediction coefficient storage unit according to the determination result 6. The image signal processing according to claim 5 , wherein the processing in the image signal processing means is controlled by selecting a prediction coefficient of any set of the prediction coefficients and supplying the prediction coefficient to the calculation means. apparatus. The prediction coefficient storage means stores a plurality of sets of prediction coefficients obtained by learning using different types of images,
The image signal processing means converts an image signal supplied from a reproduction device that reproduces an image signal recorded on a recording medium into the second image signal as the first image signal,
The control means discriminates the reproduction speed of the image signal in the reproduction apparatus based on the operation command received by the second command reception means, and stores it in the prediction coefficient storage means according to the discrimination result. by supplying to said calculating means to select a prediction coefficient of either set of prediction coefficients of the plurality of sets that are, in claim 3, characterized in that to control the processing in the image signal processing unit The image signal processing apparatus described. The utilization means is:
Reproduction speed selection frequency counting means for counting the reproduction speed selection frequency at which the reproduction speed is selected based on the operation command received by the second command reception means;
The image signal processing apparatus according to claim 8 , further comprising: a reproduction speed selection frequency storage unit that stores the reproduction speed selection frequency. The prediction coefficient storage means stores a plurality of sets of prediction coefficients obtained by learning using different types of images,
The image signal processing means converts an image signal reproduced by a reproduction device that reproduces an image signal into the second image signal as the first image signal,
The control means discriminates the reproducing apparatus reproducing the image signal based on the operation command received by the second command receiving means, and stores the prediction coefficient in the prediction coefficient storage means according to the discrimination result. by supplying to said calculating means to select a prediction coefficient of either set of prediction coefficients stored plurality sets, claim 3, characterized in that to control the processing in the image signal processing unit 2. An image signal processing apparatus according to 1. The utilization means is:
Playback device selection frequency counting means for counting the playback device selection frequency selected by the playback device based on the operation command received by the second command receiving means;
The image signal processing device according to claim 10 , further comprising: a playback device selection frequency storage unit that stores the playback device selection frequency. The prediction coefficient storage means stores a plurality of sets of prediction coefficients obtained by learning using different types of images,
The image signal processing means converts an image signal reproduced in a recording / reproducing apparatus that records and reproduces an image signal into the second image signal as the first image signal,
The control means discriminates the recording / reproducing apparatus reproducing an image signal based on the operation command received by the second command receiving means, and the prediction coefficient storage means according to the discrimination result Control the processing in the image signal processing means by selecting any one of the plurality of sets of prediction coefficients stored in and supplying the prediction coefficient to the computing means,
Learning means for learning a new prediction coefficient using an image signal before being recorded in the recording / reproducing apparatus and an image signal recorded and reproduced in the recording / reproducing apparatus;
The image signal processing apparatus according to claim 3 , further comprising: an updating unit that updates a storage content of the prediction coefficient storage unit with the new prediction coefficient. The image processing apparatus further includes resizing means for resizing the image signal and outputting the resized image signal,
The execution unit executes a process of setting a resizing rate when the image is resized by the resizing unit based on the operation command received by the first command receiving unit.
The image signal processing apparatus according to claim 4 , wherein the image signal processing unit obtains the second image signal by using the resized image signal as the first image signal. An image signal processing apparatus comprising utilization means used for image signal processing for processing an image signal , wherein the utilization means is constituted by a semiconductor chip and is detachable from the image signal processing apparatus In the image signal processing method of the processing device ,
A first command receiving step for receiving an operation command from the outside;
An execution step of executing processing according to the operation command received in the processing of the first command receiving step;
An image signal processing step for processing the image signal;
In the utilization means,
A second command receiving step for receiving the same operation command as the operation command received in the first command receiving step;
And a control step of controlling processing in the image signal processing step based on the operation command received in the processing of the second command receiving step. An image signal processing apparatus comprising utilization means used for image signal processing for processing an image signal , wherein the utilization means is constituted by a semiconductor chip and is detachable from the image signal processing apparatus A program to be executed by a processing device ,
A first command receiving step for receiving an operation command from the outside;
An execution step of executing processing according to the operation command received in the processing of the first command receiving step;
An image signal processing step for processing the image signal;
In the utilization means,
A second command receiving step for receiving the same operation command as the operation command received in the first command receiving step;
And a control step for controlling the processing in the image signal processing step based on the operation command received in the processing of the second command receiving step. Recording medium. An image signal processing apparatus comprising utilization means used for image signal processing for processing an image signal , wherein the utilization means is constituted by a semiconductor chip and is detachable from the image signal processing apparatus In a program to be executed by a processing device ,
A first command receiving step for receiving an operation command from the outside;
An execution step of executing processing according to the operation command received in the processing of the first command receiving step;
An image signal processing step for processing the image signal;
In the utilization means,
A second command receiving step for receiving the same operation command as the operation command received in the first command receiving step;
A program for causing a computer to execute processing including a control step of controlling processing in the image signal processing step based on the operation command received in the processing of the second command receiving step.

Images