JP2005142743A - Processing apparatus and processing method for information signal, and program for executing the processing method and medium with the program recorded thereon - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve the quality of an output by using a second information signal (HD signal) obtained by processing a first information signal (SD signal). <P>SOLUTION: A feature quantity extract circuit 117 selectively extracts a single or a plurality of pixel data located around a target position in the HD signal on the basis of the SD signal to extract a feature quantity CQ at the target position in the HD signal. A parameter decision circuit 118 decides values of parameters r, z determining a resolution of the HD signal and a noise eliminating degree to be values corresponding to the feature quantity CQ. A coefficient generating circuit 119 uses coefficient type data w<SB>i0</SB>to w<SB>i9</SB>and the values of the parameters r, z of a class to which the pixel data of the target position belong to generate coefficient data Wi of an estimate expression. An arithmetic circuit 121 uses data xi of a prediction tap and the coefficient data Wi to obtain the pixel data at the target position in the HD signal on the basis of the estimate expression. A user does not set the values of the parameters but the values of the parameters are automatically decided to be locally optimum values. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an information signal processing device and method for converting a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data, and a program for executing the processing method, The present invention relates to a medium on which the program is recorded.

  Specifically, the present invention extracts a feature amount of the target position in the second information signal based on the information data of the first information signal located around the target position in the second information signal. The second information signal is generated by generating the information data of the target position in the second information signal so that the quality of the output corresponding to the target position in the information signal is the quality corresponding to the extracted feature amount. The present invention relates to an information signal processing device and the like that improve the quality of output.

  Conventionally, for example, a format conversion for converting an SD (Standard Definition) signal called a 525i signal into an HD (High Definition) signal called a 1050i signal has been proposed. The 525i signal means an interlaced image signal having 525 lines, and the 1050i signal means an interlaced image signal having 1050 lines.

  In order to perform the format conversion as described above, the applicant first obtains the pixel data of the 1050i signal from the pixel data of the 525i signal, and the estimation formula corresponding to the phase of each pixel of the 1050i signal with respect to the pixel of the 525i signal It has been proposed to use a resolution creation technique in which the coefficient data is stored in a memory and the coefficient data is used to obtain pixel data of a 1050i signal based on an estimation formula.

  As described above, in the case of obtaining the pixel data of the 1050i signal by the estimation formula, the resolution of the image by the 1050i signal is fixed, and it is desired according to the image content or the like like the conventional adjustment of contrast, sharpness, etc. The resolution could not be achieved. Therefore, the present applicant has previously proposed an image signal conversion apparatus in which the user can arbitrarily adjust the resolution of an image to a desired value (see Patent Document 1).

JP 2002-218414 A

  However, in the image signal conversion device described in Patent Document 1, even if the value of the pixel data at the target position is large or small, that is, even if the feature amount of the target position is different, the entire screen is uniform. The coefficient data corresponding to the resolution adjusted by the above is used, and there are places where the resolution is appropriate and places where the resolution is inappropriate.

  An object of the present invention is to improve the output quality of the second information signal obtained by converting the first information signal.

  An information signal processing apparatus according to the present invention is an information signal processing apparatus that converts a first information signal made up of a plurality of information data into a second information signal made up of a plurality of information data. A feature amount extracting unit that selects information data located around a target position in the second information signal based on the selected information data, and extracts a feature amount of the target position in the second information signal based on the selected information data; Information for generating information data of the target position in the second information signal so that the quality of the output corresponding to the target position in the second information signal is the quality corresponding to the feature amount extracted by the feature amount extraction unit And data generation means.

  An information signal processing method according to the present invention is an information signal processing method for converting a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data, wherein the first information signal A feature amount extraction step of selecting information data located around a target position in the second information signal based on the signal and extracting a feature amount of the target position in the second information signal based on the selected information data And generating information data of the target position in the second information signal so that the quality of the output corresponding to the target position in the second information signal is the quality corresponding to the feature amount extracted in the feature amount extraction step. And an information data generation step.

  A program according to the present invention is for causing a computer to execute the information signal processing method described above. A computer-readable medium according to the present invention records the above-described program.

  In the present invention, the first information signal is converted into the second information signal. Each of the first and second information signals is composed of a plurality of information data. For example, the information signal is an image signal composed of a plurality of pixel data or a sound signal composed of a plurality of sound data (sampling data).

  Information data located around the target position in the second information signal is selected based on the first information signal, and the feature quantity of the target position in the second information signal is extracted based on the selected information data. The

  For example, single information data located around the target position in the second information signal is selected, and the value of the single information data is extracted as a feature amount. Further, for example, a plurality of pieces of information data located around the target position in the second information signal are selected, and an average value of the values of the plurality of pieces of information data is extracted as a feature amount.

  Further, for example, single information data located around the position of interest in the second information signal is selected, and the value of this single information data is output means for obtaining an output by the second information signal (for example, The information signal is converted into an output value based on the correspondence between the value of the information data and the output value on the display when the information signal is an image signal, and on the display when the information signal is an audio signal. The output value is extracted as a feature amount. When the information signal is an image signal, for example, a luminance value obtained by converting the value of a single pixel data is extracted as a feature amount.

  Further, for example, a plurality of pieces of information data located around the position of interest in the second information signal are selected, and the values of the plurality of pieces of information data are stored in the output means for obtaining the output by the second information signal. Based on the correspondence between the value and the output value, each is converted into an output value, and an average value of a plurality of output values obtained by the conversion is extracted as a feature amount. When the information signal is an image signal, for example, an average value of a plurality of luminance values obtained by converting values of a plurality of pixel data is extracted as a feature amount.

  As described above, when the output value is extracted as the feature amount, the output that the user is viewing is compared with the case where the single information data value or the average value of the plurality of information data values is extracted as the feature amount. A directly corresponding feature amount can be obtained, the output quality corresponding to the target position in the second information signal can be accurately controlled, and the output quality of the second information signal can be further improved.

  Information data of the target position in the second information signal is generated so that the quality of the output corresponding to the target position in the second information signal is the quality corresponding to the feature amount extracted as described above. For example, the value of a parameter indicating the quality of output by the second information signal is determined based on this feature amount. In this case, the user does not set the parameter value, and the parameter value is automatically determined locally as an optimal value.

  Based on the determined parameter value, information data of the target position in the second information signal is generated. When the image signal is an information signal, for example, the parameter value indicates the resolution of the image or the degree of noise removal by the second information signal.

  For example, coefficient data used in the estimation equation corresponding to the value of the parameter is generated, and a plurality of first information data located around the position of interest in the second information signal based on the first information signal The plurality of pieces of first information data and coefficient data are selected, and information data of the position of interest in the second information signal is calculated based on the estimation formula.

  The coefficient data used in the estimation formula is generated by a generation formula including parameters, for example. In this case, it is not necessary to store the coefficient data corresponding to each parameter value, and it is sufficient to store only the coefficient seed data that is the coefficient data of the generation formula, and the memory capacity can be saved.

  For example, when calculating the information data of the position of interest in the second information signal based on the estimation formula, the coefficient data corresponding to the class to which the information data of the position of interest in the second information signal belongs is used. The information data of the position of interest in the two information signals can be generated with high accuracy. This class is detected based on, for example, a plurality of second information data located around the position of interest in the second information signal based on the first information signal.

  According to this invention, the feature amount of the target position in the second information signal is extracted based on the information data of the first information signal located around the target position in the second information signal, and the second information The information data of the target position in the second information signal is generated so that the quality of the output corresponding to the target position in the signal becomes the quality corresponding to the extracted feature quantity, and the second information signal The output quality can be improved.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 shows a configuration of a television receiver 100 as an embodiment.

  The television receiver 100 has a function of obtaining an SD (Standard Definition) signal called a 525i signal from a broadcast signal, converting the 525i signal into an HD (High Definition) signal called a 1050i signal, and displaying an image based on the HD signal. ing. Here, the 525i signal is an interlaced image signal having 525 lines, and the 1050i signal is an interlaced image signal having 1050 lines.

  FIG. 2 shows the pixel position relationship of a frame (F) in which a 525i signal and a 1050i signal are present. The pixel position of an odd (o) field is indicated by a solid line, and the pixel position of an even (e) field is indicated by a broken line. ing. Large dots are pixels of 525i signal, and small dots are pixels of 1050i signal. As can be seen from FIG. 2, the pixel data of the 1050i signal includes line data L1 and L1 ′ at positions close to the line of the 525i signal and line data L2 and L2 ′ at positions far from the line of the 525i signal. Here, L1 and L2 are line data of odd fields, and L1 'and L2' are line data of even fields. The number of pixels in each line of the 1050i signal is twice the number of pixels in each line of the 525i signal.

  Returning to FIG. 1, the television receiver 100 is supplied with a receiving antenna 101 and a broadcast signal (RF modulation signal) received by the receiving antenna 101, and performs channel selection processing, intermediate frequency amplification processing, detection processing, and the like. A tuner unit 102 for obtaining SD signals, and a buffer memory 103 for temporarily storing the SD signals obtained by the tuner unit 102.

  The television receiver 100 also displays an image signal processing unit 104 that converts an SD signal temporarily stored in the buffer memory 103 into an HD signal, and an image based on the HD signal obtained by the image signal processing unit 104. And a display unit 105. The display unit 105 includes, for example, a CRT (Cathode-Ray Tube) display, an LCD (Liquid Crystal Display), or a PDP (Plasma Display Panel).

The operation of the television receiver 100 shown in FIG. 1 will be described.
The SD signal obtained by the tuner unit 102 is supplied to the buffer memory 103 and temporarily stored. The SD signal temporarily stored in the buffer memory 103 is supplied to the image signal processing unit 104 and converted into an HD signal. That is, the image signal processing unit 104 generates pixel data constituting the HD signal (hereinafter referred to as “HD pixel data” as appropriate) from pixel data constituting the SD signal (hereinafter referred to as “SD pixel data” as appropriate). The

  The HD signal output from the image signal processing unit 104 is supplied to the display unit 105, and an image based on the HD signal is displayed on the screen of the display unit 105.

Next, details of the image signal processing unit 104 will be described.
The image signal processing unit 104 selectively selects a plurality of SD pixel data located around the target position in the HD signal (1050i signal) based on the SD signal (525i signal) temporarily stored in the buffer memory 103. The first to third tap selection circuits 111 to 113 for taking out and outputting the data.

  The first tap selection circuit 111 selectively extracts a plurality of SD pixel data used for prediction as prediction tap data. The second tap selection circuit 112 selectively extracts a plurality of SD pixel data used for class classification corresponding to the level distribution pattern as space class tap data. 3A and 3B show examples of space class taps and prediction taps, respectively.

  The third tap selection circuit 113 selectively extracts a plurality of SD pixel data used for class classification corresponding to motion as motion class tap data. When the space class is determined using SD pixel data belonging to a plurality of fields, motion information is also included in this space class.

  Further, the image signal processing unit 104 detects the level distribution pattern of the space class tap data (SD pixel data) selectively extracted by the second tap selection circuit 112, and determines the space class based on the level distribution pattern. It has a space class detection circuit 114 that detects and outputs the class information.

  In the space class detection circuit 114, for example, an operation is performed to compress each SD pixel data from 8-bit data to 2-bit data. The space class detection circuit 114 outputs compressed data corresponding to each SD pixel data as class information of the space class. In the present embodiment, data compression is performed by ADRC (Adaptive Dynamic Range Coding). In addition to ADRC, DPCM (predictive coding), VQ (vector quantization), or the like may be used as the data compression means.

Originally, ADRC is an adaptive requantization method developed for high performance coding for VTR (Video Tape Recorder), but it can efficiently express local patterns of signal level with short word length. It is suitable for use in data compression. When ADRC is used, the maximum value of space class tap data (SD pixel data) is MAX, the minimum value is MIN, the dynamic range of space class tap data is DR (= MAX−MIN + 1), and the number of requantization bits Is P, the requantized code qi as compressed data is obtained by the calculation of the equation (1) for each SD pixel data ki as the space class tap data. However, in the expression (1), [] means a truncation process. When there are Na SD pixel data as the space class tap data, i = 1 to Na.
qi = [(ki−MIN + 0.5) * 2 ^P / DR] (1)

  Further, the image signal processing unit 104 detects a motion class mainly representing the degree of motion from the motion class tap data (SD pixel data) selectively extracted by the third tap selection circuit 113, and A motion class detection circuit 115 that outputs class information is provided.

  In this motion class detection circuit 115, the inter-frame difference is calculated from the motion class tap data (SD pixel data) mi, ni selectively extracted by the third tap selection circuit 113, and the average of the absolute values of the differences is further calculated. Threshold processing is performed on the value to detect a motion class that is an index of motion. That is, in the motion class detection circuit 115, the average value AV of the absolute value of the difference is calculated by the equation (2). For example, when 12 pieces of SD pixel data m1 to m6 and n1 to n6 are extracted by the third tap selection circuit 113, Nb in the equation (2) is 6.

  In the motion class detection circuit 115, the average value AV calculated as described above is compared with one or a plurality of threshold values to obtain class information MV of the motion class. For example, three thresholds th1, th2, th3 (th1 <th2 <th3) are prepared, and when four motion classes are detected, when AV ≦ th1, MV = 0 and th1 <AV ≦ th2 Is MV = 2 when MV = 1, th2 <AV ≦ th3, and MV = 3 when th3 <AV.

  Further, the image signal processing unit 104 has a class synthesis circuit 116. Based on the requantization code qi as the class information of the space class output from the space class detection circuit 114 and the class information MV of the motion class output from the motion class detection circuit 115, the class synthesis circuit 116 A class code CL indicating the class to which the pixel data of the target position in (the HD pixel data to be created) belongs is obtained. In this class synthesis circuit 116, the calculation of the class code CL is performed by the equation (3). In equation (3), Na represents the number of space class tap data (SD pixel data), and P represents the number of requantization bits in ADRC.

  Further, the image signal processing unit 104 includes a feature amount extraction circuit 117. This feature amount extraction circuit 117 is based on the SD signal (525i signal) temporarily stored in the buffer memory 103, and single or plural SD pixel data located around the target position in the HD signal (1050i signal). Is selectively extracted, and the feature amount CQ of the target position in the HD signal is extracted based on the extracted SD pixel data. FIG. 3C shows an example of a plurality of SD pixel data selectively extracted.

The feature quantity extraction circuit 117 extracts the feature quantity CQ, for example, as in the following (a) to (d).
(A) The feature amount extraction circuit 117 extracts a single SD pixel data value that is selectively extracted as a feature amount CQ.
(B) The feature amount extraction circuit 117 extracts an average value of the values of the plurality of SD pixel data selectively extracted as the feature amount CQ.
(C) The feature amount extraction circuit 117 changes the value of the single SD pixel data that is selectively extracted to the correspondence between the pixel data value (pixel value) in the display unit 105 and the luminance value as the output value. Based on this, the brightness value is converted, and this brightness value is extracted as a feature value CQ.
(D) The feature amount extraction circuit 117 determines the values of the plurality of SD pixel data that are selectively extracted based on the correspondence between the pixel data values (pixel values) in the display unit 105 and the luminance values as output values. Each is converted into a luminance value, and an average value of the plurality of luminance values is extracted as a feature amount CQ.

  In the display unit 105, the luminance value is not generally in a linear relationship with the pixel value, but has a correspondence relationship as shown in the equation (4) and FIG. In equation (4), y is a luminance value, x is a pixel value, A is a maximum luminance value, and γ is a gamma value. Although detailed description is omitted, it is well known that the gamma value γ varies depending on the type of display constituting the display unit 105.

  When the feature value extraction circuit 117 extracts the brightness value as the feature value, for example, the feature value extraction circuit 117 calculates the brightness value from the pixel value based on the above-described equation (4), or creates a table indicating the correspondence between the pixel value and the brightness value. A luminance value is obtained from the pixel value using a table prepared in advance.

  In addition, the image signal processing unit 104 includes a parameter determination circuit 118 that determines the values of parameters r and z indicating the image quality of an image based on the HD signal based on the feature value CQ extracted by the feature value extraction circuit 117. Yes. Here, the parameter r determines the resolution of the image based on the HD signal, and the parameter z determines the noise removal degree of the image based on the HD signal. For example, the parameter determination circuit 118 prepares a table indicating the correspondence between the feature quantity CQ and the values of the parameters r and z, and determines the values of the parameters r and z using the table.

  FIG. 5A shows an example of the relationship between the feature value CQ and the value of the parameter r. In this case, the value of the parameter r is changed in the direction of decreasing the resolution in a bright portion where the feature amount CQ is large, that is, the pixel value or luminance value is large and bright. FIG. 5B shows an example of the relationship between the feature amount CQ and the value of the parameter z. In this case, in the dark portion where the feature amount CQ is small, that is, the pixel value or the luminance value is small, the value of the parameter z is changed in a direction to increase the degree of noise removal.

  FIG. 6 shows an example of the relationship between the feature amount CQ extracted as described above (a) to (d) and the values of the parameters r and z. Here, the parameters r and z each take a value between 0 and 1.

  Further, the image signal processing unit 114 includes a coefficient generation circuit 119 and a ROM 120. The coefficient generation circuit 119 and the ROM 120 constitute coefficient data generation means. The coefficient generation circuit 119 generates a plurality of coefficient data Wi (i = 1 to n) used in the estimation formula used in the estimation prediction calculation circuit 121 described later. Based on the class code CL acquired by the class synthesis circuit 116 and the values of the parameters r and z determined by the parameter determination circuit 118, the coefficient generation circuit 119 uses the generation formula (5) to generate coefficient data Wi (i = N).

The ROM 120 stores, for each class, coefficient seed data w _{i0 to} w _i9 (i = 1 to n), which is coefficient data of the generation formula (5). A method of generating the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) will be described later. The coefficient generation circuit 119 acquires the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) of the class indicated by the class code CL from the ROM 120, and the coefficient seed data w _{i0 to} w _i9 (i = 1 to n). ) And the values of the parameters r and z, the coefficient data Wi (i = n) is obtained by the generation equation (5).

  As described above, when the 525i signal is converted into the 1050i signal, it is necessary to obtain four pixels of the 1050i signal corresponding to one pixel of the 525i signal in each of the odd and even fields. In this case, the four pixels in the 2 × 2 unit pixel block constituting the 1050i signal in each of the odd and even fields have different phase shifts with respect to the central prediction tap.

FIG. 7 shows a phase shift from the center prediction tap SD ₀ in the four pixels HD _{1 to} HD ₄ in the 2 × 2 unit pixel block constituting the 1050i signal in the odd field. Here, the position of HD ₁ ~HD _4, respectively, k ₁ to k ₄ in the horizontal direction from the position of the SD _0, it is offset in the vertical direction by m ₁ ~m _4.

FIG. 8 shows a phase shift from the center prediction tap SD ₀ ′ in the four pixels HD ₁ ′ to HD ₄ ′ in the 2 × 2 unit pixel block constituting the 1050i signal in the even field. Here, the position of HD ₁ '~HD _4', respectively, SD ₀ ~k ₄ 'k ₁ in the horizontal direction from the position of'deviates', vertically m ₁ 'only ~m _4'.

Therefore, the coefficient generation circuit 119 individually generates coefficient data Wi (i = n) corresponding to four output pixels (HD _{1 to} HD _{4 in} the odd field and HD ₁ ′ to HD ₄ ′ in the even field). When the coefficient generation circuit 119 obtains coefficient data Wi (i = n) corresponding to each output pixel, the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) corresponding to each output pixel is stored in the ROM 120. Get from. Accordingly, the ROM 120 stores the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) of the class and output pixels (see HD _{1 to} HD ₄ in FIG. 7 and HD ₁ ′ to HD ₄ ′ in FIG. 8). Each combination is stored.

  In addition, the image signal processing unit 104 includes an estimated prediction calculation circuit 121. The estimated prediction calculation circuit 121 includes prediction tap data (a plurality of SD pixel data) xi selectively extracted by the first tap selection circuit 111 and coefficient data Wi generated by the coefficient generation circuit 119 ( 6) Pixel data of the HD signal to be created (pixel data at the target position) is obtained based on the estimation formula of 6).

As described above, when an SD signal is converted into an HD signal, four pixels of the HD signal (HD _{1 to} HD ₄ in FIG. 7 and HD ₁ ′ to HD ₄ ′ in FIG. 8) with respect to one pixel of the SD signal. See). In the estimated prediction calculation circuit 121, pixel data is generated for each 2 × 2 unit pixel block constituting the HD signal.

That is, the estimated prediction calculation circuit 121 receives the prediction tap data xi corresponding to four pixels (target pixel) in the unit pixel block from the first tap selection circuit 111 and the unit pixel block from the coefficient generation circuit 119. Coefficient data Wi corresponding to the four pixels to be configured is supplied. Then, in the estimation predictive calculating circuit 121, four pixels data y ₁ ~y ₄ of constituting the unit pixel block is individually calculated by the estimate equation of each above (6).

Further, the image signal processing unit 104, the estimated prediction calculation circuit 121 are sequentially output from the post-processing output in the format of the 1050i signal in line sequence data y ₁ ~y ₄ of 4 pixels in the unit pixel block circuit 122 have.

Next, the operation of the image signal processing unit 104 shown in FIG. 1 will be described.
In the second tap selection circuit 112, based on the SD signal (525i signal) temporarily stored in the buffer memory 103, four pixels (unit pixels block) constituting the HD signal (1050i signal) to be created ( A plurality of SD pixel data located around the pixel of interest) is selectively extracted as space class tap data. The space class tap data selectively extracted by the second tap selection circuit 112 is supplied to the space class detection circuit 114. In this space class detection circuit 114, each SD pixel data as space class tap data is subjected to ADRC processing and re-used as class information of a space class (mainly class classification for waveform expression in space). A quantization code qi is obtained (see equation (1)).

  Further, in the third tap selection circuit 113, 4 in the unit pixel block constituting the HD signal (1050i signal) to be created based on the SD signal (525i signal) temporarily stored in the buffer memory 103. A plurality of SD pixel data located around the pixel (the pixel at the target position) is selectively extracted as motion class tap data. The motion class tap data selectively extracted by the third tap selection circuit 113 is supplied to the motion class detection circuit 115. In this motion class detection circuit 115, class information MV of a motion class (mainly class classification for representing the degree of motion) is obtained from each SD pixel data as motion class tap data.

  The motion information MV and the above-described requantization code qi are supplied to the class synthesis circuit 116. In this class synthesizing circuit 116, from the motion information MV and the requantization code qi, for each unit pixel block constituting the HD signal (1050i signal) to be created, four pixels (target pixel) in the unit pixel block are obtained. A class code CL indicating the class to which it belongs is obtained (see equation (3)). The class code CL is supplied to the coefficient generation circuit 119.

  Based on the SD signal temporarily stored in the buffer memory 103, the feature quantity extraction circuit 117 selectively extracts single or plural SD pixel data located around the target position in the HD signal. Based on the extracted SD pixel data, the feature amount CQ of the target position in the HD signal is extracted. The feature amount CQ includes, for example, a single SD pixel data value, an average value of a plurality of SD pixel data values, a luminance value obtained by converting a single SD pixel data value, and a plurality of SD pixel data. The average value of a plurality of luminance values obtained by converting each of the values.

  The feature quantity CQ extracted by the feature quantity extraction circuit 117 in this way is supplied to the parameter determination circuit 118. The parameter determination circuit 118 determines the values of the parameters r and z corresponding to the feature quantity CQ based on, for example, a table (see FIGS. 5A and 5B) showing the correspondence between the feature quantity CQ and the values of the parameters r and z. . Thus, the values of the parameters r and z determined by the parameter determination circuit 118 are supplied to the coefficient generation circuit 119.

In the coefficient generation circuit 119, the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) of the class indicated by the class code CL is acquired from the ROM 120, and the coefficient seed data w _{i0 to} w _i9 (i = 1 to n). ) And the values of the parameters r and z are used, and coefficient data Wi (i = n) is generated by the generation equation (5). In this case, the coefficient generation circuit 119 individually generates coefficient data Wi (i = 1 to n) corresponding to the four output pixels (HD _{1 to} HD ₄ or HD ₁ ′ to HD ₄ ′).

  Thus, the coefficient data Wi for the four output pixels generated by the coefficient generation circuit 119 is supplied to the estimated prediction calculation circuit 121. Further, in the first tap selection circuit 111, based on the SD signal, a plurality of pieces of SD pixel data located around four pixels (pixels at the target position) in the unit pixel block constituting the HD signal to be created are stored. It is selectively extracted as the prediction tap data xi. The prediction tap data xi is supplied to the estimated prediction calculation circuit 121.

The estimated prediction calculation circuit 121 generates an HD signal to be generated based on the estimation equation (6) from the prediction tap data xi and the coefficient data Wi for four output pixels supplied from the coefficient generation circuit 119. data y ₁ ~y ₄ of 4 pixels in the unit pixel block constituting (a pixel position of interest) are individually calculated. Data y _{1 to} y ₄ sequentially output from the estimated prediction calculation circuit 121 is supplied to the post-processing circuit 122.

In the post-processing circuit 122, the data y _{1 to} y ₄ sequentially supplied from the estimated prediction calculation circuit 121 are line-sequentially output in the format of 1050i signal. That is, the post-processing circuit 122 outputs a 1050i signal as an HD signal.

  As described above, the image signal processing unit 104 shown in FIG. 1 extracts the feature amount CQ of the target position in the HD signal based on the SD signal, and the image quality (resolution and noise removal) of the HD signal using this feature amount CQ. The values of the parameters r and z that determine the degree) are determined, and pixel data of the target position in the HD signal is generated so that the image quality of the image corresponding to the target position in the HD signal becomes the image quality corresponding to the feature amount CQ. The

  For example, the value of the parameter r changes in the direction of decreasing the resolution in a bright portion of the image having a large pixel value or luminance value as the feature amount CQ. Further, for example, in a dark portion where the pixel value or luminance value as the feature amount CQ is small and dark, the value of the parameter z changes in a direction to increase the noise removal degree.

  Therefore, in the image signal processing unit 104 shown in FIG. 1, the user sets the values of the parameters r and z and does not use the coefficient data Wi corresponding to the values of the parameters r and z uniformly on the entire screen. The values of parameters r and z are automatically determined to be optimal values locally. Therefore, the image quality of the HD signal obtained by the image signal processing unit 104 can be improved.

  Further, according to the feature value using the luminance value as the feature value CQ, the user can view the feature value CQ as compared with the feature value CQ using a pixel value (a single pixel data value or an average value of a plurality of pixel data values). It is possible to obtain a feature amount CQ that directly corresponds to an existing image, to control the image quality of the image corresponding to the target position in the HD signal with high accuracy, and to further improve the image quality of the image by the HD signal.

Next, a method of generating coefficient class data w _{i0 to} w _i9 (i = 1 to n) of each class stored in the ROM 120 will be described.
Here, for the following explanation, tj (j = 0 to 9) is defined as in the equation (7).
t ₀ = 1, t ₁ = r, t ₂ = z, t ₃ = r ² , t ₄ = rz, t ₅ = z ² ,
^{_{t 6 = r 3, t 7}} = r 2 z, t 8 = rz 2, t 9 = z 3
... (7)
Using this equation (7), equation (5) can be rewritten as equation (8).

Finally, the undetermined coefficient w _ij is obtained by learning. That is, for each combination of class and output pixel, a coefficient value that minimizes the square error is determined using a plurality of SD pixel data and HD pixel data. This is a so-called least square method. Assuming that the learning number is m, the residual in the kth (1 ≦ k ≦ m) learning data is e _k , and the sum of the square errors is E, E is (9) using the equations (5) and (6). ) Expression. Here, x _ik represents k-th pixel data at the i-th predicted tap position of the SD image, and y _k represents pixel data of the corresponding k-th HD image.

The solution according to the minimum square method, determine the w _ij such that 0 is partial differentiation by (9) of w _ij. This is shown by equation (10).

Here, when X _ipjq and Y _ip are defined as in the expressions (11) and (12), the expression (10) is rewritten as the expression (13) using a matrix.

This equation (13) is a normal equation for calculating coefficient seed data. Coefficient seed data w _{i0 to} w _i9 (i = 1 to n) can be obtained by solving this normal equation by a general solution method such as a sweep-out method (Gauss-Jordan elimination method).

  FIG. 9 shows the concept of the above-described coefficient seed data generation method. A plurality of SD signals as student signals are generated from the HD signals as teacher signals. Here, SD signals having different resolutions are generated by changing the frequency characteristics of the thinning filter used when the SD signal is generated from the HD signal.

  Coefficient seed data having different effects of increasing the resolution can be generated by SD signals having different resolutions. For example, when there is an SD signal from which an image with a large degree of blur can be obtained and an SD signal from which an image with a small degree of blur can be obtained, coefficient seed data having a strong effect of increasing the resolution by learning with the SD signal from which an image with a large degree of blur can be obtained Is generated, and coefficient seed data having a weak effect of increasing the resolution is generated by learning with the SD signal from which an image with a small degree of blur can be obtained.

  Further, by adding noise to each of the SD signals having different resolutions, an SD signal with noise added is generated. By varying the amount of noise to be added, SD signals having different noise amounts are generated, thereby generating coefficient seed data having different noise removal effects. For example, if there is an SD signal with a lot of noise added and an SD signal with a little noise added, coefficient seed data with a strong noise removal effect is generated by learning with the SD signal with a lot of noise added, and SD with a little noise added. Coefficient seed data having a weak noise removal effect is generated by learning with a signal.

As the amount of noise to be added, for example, as shown in equation (14), when generating the pixel value x ′ of the SD signal to which noise n is added by adding noise n to the pixel value x of the SD signal, G is variable. To adjust the amount of noise.
x ′ = x + G · n (14)

  For example, the value of the parameter r for varying the frequency characteristic is varied in 11 steps from 0 to 1.0 in 0.1 steps, and the value of the parameter z for varying the amount of noise added is varied from 0 to 1.0 to 0.1. It is variable to 11 steps in one step, and a total of 121 types of SD signals are generated. Learning is performed between the plurality of SD signals generated in this way and the HD signal to generate coefficient seed data. The parameters r and z correspond to the parameters r and z in the parameter determination circuit 118 in FIG.

Next, the coefficient seed data generation device 150 for generating the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) stored in the ROM 120 of the image signal processing unit 104 described above will be described. FIG. 10 shows the configuration of the coefficient seed data generation device 150.

  This coefficient seed data generation device 150 performs an horizontal thinning and vertical thinning process on the input terminal 151 to which an HD signal (1050i signal) as a teacher signal is input, and an SD signal as a student signal. And an SD signal generation circuit 152 for obtaining a signal. The SD signal generation circuit 152 is supplied with parameters r and z. Corresponding to the value of the parameter r, the frequency characteristic of the decimation filter used when generating the SD signal from the HD signal is varied. Further, the amount of noise added to the SD signal is varied corresponding to the value of the parameter z.

  The coefficient seed data generation device 150 selectively extracts and outputs data of a plurality of SD pixels located around the target position in the HD signal based on the SD signal output from the SD signal generation circuit 152. The first to third tap selection circuits 153 to 155 are provided. These first to third tap selection circuits 153 to 155 are configured similarly to the first to third tap selection circuits 111 to 113 of the image signal processing unit 104 described above.

  The coefficient seed data generation device 150 detects the level distribution pattern of the space class tap data (a plurality of SD pixel data) selectively extracted by the second tap selection circuit 154, and based on the level distribution pattern. A space class detection circuit 157 that detects the space class and outputs the class information is provided. The space class detection circuit 157 is configured similarly to the space class detection circuit 114 of the image signal processing unit 104 described above. From this space class detection circuit 157, a requantization code qi for each SD pixel data as space class tap data is output as class information indicating a space class.

  The coefficient seed data generation device 150 detects a motion class mainly for representing the degree of motion from the motion class tap data (a plurality of SD pixel data) selectively extracted by the third tap selection circuit 155. And a motion class detection circuit 158 that outputs the class information MV. The motion class detection circuit 158 is configured in the same manner as the motion class detection circuit 115 of the image signal processing unit 104 described above. In this motion class detection circuit 158, the inter-frame difference is calculated from the motion class tap data (SD pixel data) selectively extracted by the third tap selection circuit 155, and the difference between the absolute values of the absolute values of the difference is calculated. Then, threshold processing is performed to detect a motion class that is an index of motion.

  Also, the coefficient seed data generation device 150 is based on the requantization code qi as the class information of the space class output from the space class detection circuit 157 and the class information MV of the motion class output from the motion class detection circuit 158. , A class combining circuit 159 for obtaining a class code CL indicating a class to which the pixel data at the target position in the HD signal (1050i signal) belongs. The class synthesis circuit 159 is also configured in the same manner as the class synthesis circuit 116 of the image signal processing unit 104 described above.

Further, the coefficient seed data generation device 150 has a normal equation generation unit 160. The normal equation generation unit 160 includes each HD pixel data y as target pixel data obtained from the HD signal supplied to the input terminal 151, and a first tap selection circuit 153 corresponding to each HD pixel data y. Class and output pixel combination from the prediction tap data xi selectively extracted in step (b), the class code CL obtained by the class synthesis circuit 159 corresponding to each HD pixel data y, and the values of the parameters r and z. Every time, a normal equation (see equation (13)) for obtaining coefficient seed data w _{i0 to} w _i9 (i = 1 to n) of each class is generated.

In this case, learning data is generated by a combination of one HD pixel data y and prediction tap data (a plurality of SD pixel data) xi corresponding thereto, but an HD signal as a teacher signal and a student signal as A large amount of learning data is generated for each class with the SD signal. Thereby, the normal equation generation unit 160 generates a normal equation for obtaining coefficient seed data w _{i0 to} w _i9 (i = 1 to n) for each class.

In this case, the normal equation generation unit 160 generates a normal equation for each output pixel (see HD _{1 to} HD ₄ in FIG. 7 and HD ₁ ′ to HD ₄ ′ in FIG. 8). For example, the normal equation corresponding to HD ₁ is generated from learning data composed of HD pixel data y whose deviation value with respect to the center prediction tap has the same relationship as HD1. As a result, the normal equation generation unit 160 generates a normal equation for each combination of class and output pixel.

In addition, the coefficient seed data generation device 150 includes a coefficient seed data determination unit 161 and a coefficient seed memory 162. The coefficient seed data determination unit 161 receives supply of normal equation data from the normal equation generation unit 160, solves the normal equation by a sweep-out method or the like, and generates coefficient seed data w _{i0 to} w _{i9 for} each combination of class and output pixel _. (I = 1 to n) is obtained. The coefficient seed memory 162 stores the coefficient seed data w _{i0 to} w _i9 (i = 1 to n) obtained by the coefficient seed data determining unit 161.

The operation of the coefficient seed data generation device 150 shown in FIG. 10 will be described.
The SD signal generation circuit 152 performs horizontal and vertical thinning processing on the HD signal input to the input terminal 151 to generate an SD signal as a student signal. In this case, parameters r and z are supplied as control signals to the SD signal generation circuit 152, and a plurality of SD signals whose frequency characteristics and noise addition amount are changed stepwise are sequentially generated.

  Further, from the SD signal (525i signal) generated by the SD signal generation circuit 152, the second tap selection circuit 154 uses the data of the space class tap (SD pixel) located around the position of interest in the HD signal (1050i signal). Data) is selectively retrieved. The space class tap data (SD pixel data) selectively extracted by the second tap selection circuit 154 is supplied to the space class detection circuit 157. In this space class detection circuit 157, each SD pixel data as space class tap data is subjected to ADRC processing to be re-used as class information of a space class (mainly class classification for waveform expression in space). A quantization code qi is obtained (see equation (1)).

  Further, from the SD signal generated by the SD signal generation circuit 152, the third tap selection circuit 155 selectively extracts data of the motion class tap (SD pixel data) located around the target pixel related to the HD signal. It is. The motion class tap data (SD pixel data) selectively extracted by the third tap selection circuit 155 is supplied to the motion class detection circuit 158. In this motion class detection circuit 158, class information MV of a motion class (mainly class classification for representing the degree of motion) is obtained from each SD pixel data as motion class tap data.

  The class information MV and the above-described requantization code qi are supplied to the class synthesis circuit 159. The class synthesis circuit 159 obtains a class code CL indicating the class to which the pixel data at the position of interest in the HD signal (1050i signal) belongs from the class information MV and the requantization code qi (see equation (3)). .

  Further, from the SD signal generated by the SD signal generation circuit 152, the first tap selection circuit 153 selectively extracts data of predicted taps (SD pixel data) located around the target position in the HD signal.

Then, each HD pixel data y as pixel data at the target position obtained from the HD signal supplied to the input terminal 151 and the first tap selection circuit 153 selectively corresponding to each HD pixel data y. From the prediction tap data xi to be extracted, the class code CL output from the class synthesis circuit 159 corresponding to each HD pixel data y, and the values of the parameters r and z, the normal equation generation unit 160 determines the class and For each combination of output pixels, a normal equation (see equation (13)) for generating coefficient seed data w _{i0 to} w _i9 (i = 1 to n) is generated.

The coefficient seed data determination unit 161 solves each normal equation to obtain coefficient seed data w _{i0 to} w _i9 (i = 1 to n). The coefficient seed data w _{i0 to} w _i9 (i = 1 to n). ) Is stored in the coefficient seed memory 162.

As described above, in the coefficient seed data generation device 150 shown in FIG. 10, coefficient seed data w _{i0 to} w _i9 (for each class and output pixel combination stored in the ROM 120 of the image signal processing unit 104 shown in FIG. i = 1 to n) can be generated.

  Note that the processing in the image signal processing unit 104 of FIG. 1 can be realized by software, for example, by an image signal processing device 300 as shown in FIG. First, the image signal processing apparatus 300 shown in FIG. 11 will be described. The image signal processing apparatus 300 includes a CPU 301 that controls the operation of the entire apparatus, a ROM (read only memory) 302 that stores an operation program of the CPU 301, coefficient seed data, and the like, and a RAM ( random access memory) 303. These CPU 301, ROM 302, and RAM 303 are each connected to a bus 304.

  The image signal processing apparatus 300 includes a hard disk drive (HDD) 305 as an external storage device and a drive 307 that drives a removable disk 306. These drives 305 and 307 are each connected to a bus 304.

  In addition, the image signal processing apparatus 300 includes a communication unit 308 that is connected to a communication network 400 such as the Internet by wire or wirelessly. The communication unit 308 is connected to the bus 304 via the interface 309.

  In addition, the image signal processing device 300 includes a user interface unit. The user interface unit includes a remote control signal receiving circuit 310 that receives a remote control signal RM from the remote control transmitter 320, and a display 311 that includes an LCD (liquid crystal display) or the like. The receiving circuit 310 is connected to the bus 304 via the interface 312, and similarly the display 311 is connected to the bus 304 via the interface 313.

  The image signal processing apparatus 300 also has an input terminal 314 for inputting an SD signal and an output terminal 315 for outputting an HD signal. The input terminal 314 is connected to the bus 304 via the interface 316, and similarly, the output terminal 315 is connected to the bus 304 via the interface 317.

  Here, instead of storing the processing program and coefficient seed data in advance in the ROM 302 as described above, for example, they are downloaded from the communication network 400 such as the Internet via the communication unit 308 and stored in the HDD 305, RAM 303, etc. It can also be used. Further, these processing programs, coefficient seed data, and the like may be provided on the disk 306.

  Further, instead of inputting the SD signal to be processed from the input terminal 314, it may be recorded in the HDD 305 in advance or downloaded from the communication network 400 such as the Internet via the communication unit 308. Further, instead of outputting the processed HD signal to the output terminal 315 or in parallel therewith, it is supplied to the display 311 for image display, further stored in the HDD 305, or via the communication unit 308 such as the Internet. It may be sent to the communication network 400.

  A processing procedure for obtaining an HD signal from an SD signal in the image signal processing apparatus 300 shown in FIG. 11 will be described with reference to the flowchart of FIG. First, in step ST1, processing is started, and in step ST2, SD pixel data for one frame or one field is input. When the SD pixel data is input from the input terminal 314, the SD pixel data is temporarily stored in the RAM 303. If this SD pixel data is recorded in the HDD 305, this SD pixel data is read from the HDD 305 and temporarily stored in the RAM 303.

  In step ST3, it is determined whether or not processing of all frames or fields of SD pixel data has been completed. When the process is finished, the process ends in step ST4. On the other hand, when the process is not finished, the process proceeds to step ST5.

  In this step ST5, a plurality of SD pixel data as class tap and prediction tap data is acquired from the SD pixel data for one field or one frame input in step ST2 corresponding to the target position in the HD signal. Further, single or plural SD pixel data for extracting the feature amount is acquired.

  Next, in step ST6, it is determined whether or not the processing for obtaining HD pixel data has been completed in all areas of the SD pixel data input in step ST2. If completed, the process returns to step ST2 and proceeds to the input processing of SD pixel data for the next one frame or one field. On the other hand, when the process is not completed, the process proceeds to step ST7.

  In step ST7, based on the plurality of SD pixel data as the class tap data acquired in step ST5, a class code CL indicating the class to which the pixel data at the target position in the HD signal belongs is generated. In step ST8, the feature quantity CQ is extracted based on the single or plural SD pixel data acquired in step ST5. Further, in step ST9, the values of the parameters r and z are determined based on the feature quantity CQ extracted in step ST8. In this case, for example, the values of the parameters r and z are determined using a table (see FIGS. 5A and 5B) indicating the correspondence between the feature amount CQ and the values of the parameters r and z stored in the ROM 302, for example.

Next, in step ST10, the coefficient seed data w _i0 to w _i9 in the class indicated by the generated class code CL, and parameter r determined in step ST9, the value of z used in step ST7, the above (5) Based on the formula generation formula, coefficient data Wi used in the estimation formula (6) is generated.

  Next, in step ST11, using the prediction tap data xi acquired in step ST5 and the coefficient data Wi generated in step ST10, the pixel data of the target position in the HD signal based on the estimation formula of equation (6) Is generated. After that, the process returns to step ST5, and the process proceeds to the next target position in the HD signal.

  In this way, by performing processing according to the flowchart shown in FIG. 12, it is possible to process the SD pixel data constituting the input SD signal and obtain HD pixel data constituting the HD signal. As described above, the HD signal obtained by such processing is output to the output terminal 315, supplied to the display 311 to display an image, and further recorded on the HDD 305.

  Although illustration of the processing device is omitted, the processing in the coefficient seed data generation device 150 in FIG. 10 can be realized by software.

A processing procedure for generating coefficient seed data will be described with reference to the flowchart of FIG.
First, in step ST21, processing is started, and in step ST22, an image quality pattern (specified by the values of parameters r and z) used for learning is selected. In step ST23, it is determined whether learning has been completed for all image quality patterns. If learning has not been completed for all image quality patterns, the process proceeds to step ST24.

  In step ST24, known HD pixel data is input for one frame or one field. In step ST25, it is determined whether or not processing has been completed for HD pixel data of all frames or all fields. When the process is completed, the process returns to step ST22, the next image quality pattern is selected, and the same process as described above is repeated. On the other hand, when not completed, the process proceeds to step ST26.

  In step ST26, SD pixel data is generated from the HD pixel data input in step ST24 based on the image quality pattern selected in step ST22. In step ST27, a plurality of pieces of pixel data as class tap and prediction tap data are acquired from the SD pixel data generated in step ST26 in correspondence with the target position in the HD signal.

  In step ST28, it is determined whether or not the learning process has been completed in all regions of the generated SD pixel data. When the learning process is finished, the process returns to step ST24, the next one frame or one field of HD pixel data is input, the same process as described above is repeated, and the learning process is finished. If not, the process proceeds to step ST29.

  In this step ST29, the class code CL is generated from the SD pixel data of the class tap acquired in step ST27. Then, in step ST30, among the HD pixel data for one frame or one field input in step ST24, a plurality of HD pixel data at the target position in the HD signal, and a plurality of prediction tap data acquired in step ST27. Based on the SD pixel data, the values of the parameters r and z for specifying the image quality pattern in step ST22, and the class code CL generated in step ST29, the normal equation of the class indicated by the class code CL (see equation (13)) Add the process. Thereafter, the process returns to step ST27, and the process moves to the next target position in the HD signal.

If learning for all image quality patterns is completed in step ST23, the process proceeds to step ST31. In step ST31, by solving the normal equation for each class in the sweeping-out method etc., to calculate the coefficient seed data w _i0 to w _i9 for each class at step ST32, the coefficient seed data w _i0 to w _i9 in the memory After that, the process ends at step ST33.

In this way, by performing processing according to the flowchart shown in FIG. 13, the coefficient seed data w _{i0 to} w _i9 can be obtained by the same method as the coefficient seed data generation apparatus 150 shown in FIG.

  In the above-described embodiment, the pixel value or the luminance value is extracted based on single or plural SD pixel data located around the target position in the HD signal as the feature amount CQ of the target position in the HD signal. However, the feature amount CQ is not limited to a pixel value or a luminance value. That is, the feature amount CQ is obtained by controlling the image quality (resolution, noise removal degree, etc.) of the image corresponding to the target position in the HD signal so that the image quality corresponds to the feature amount CQ. Any device capable of improving the image quality is acceptable.

  For example, it is conceivable to use a high frequency component, a dynamic range, or the like obtained from a plurality of SD pixel data as the feature amount CQ. For example, when the SD signal is composed of red (R), green (G), and blue (B) color signals, or a luminance signal Y, a blue difference signal U, and a red difference signal V, these colors are used. The feature amount CQ may be extracted using a space. For example, as the feature amount CQ, as shown in FIG. 14, information (color space information) indicating where the red, green, and blue color signals (r, g, b) at the target position are in the RGB color space. ) May be extracted as the feature amount CQ. A color space other than RGB and YUV can be used.

  In the above-described embodiment, the values of the parameters r and z indicating the image quality of the HD signal are determined based on the feature quantity CQ, and the values of the parameters r and z are used to determine the target position in the HD signal. The image quality (resolution, noise removal degree) of the corresponding image is automatically controlled so that the image quality corresponds to the feature amount CQ. However, without determining the values of the parameters r and z based on the feature value CQ in this way, the image quality (resolution, noise removal degree) of the image corresponding to the target position in the HD signal based on the feature value CQ itself. Can be automatically controlled so that the image quality corresponding to the feature amount CQ is obtained.

Also, in the above-described embodiment showed that the coefficient seed data w _i0 to w _i9 is coefficient data in the production equation for producing coefficient data Wi to ROM120 of the image signal processing unit 104 is stored. Thereby, memory can be saved.

  However, it is also conceivable that coefficient data Wi itself corresponding to each combination of class and parameter r, z values is stored in the ROM 120. In that case, the image signal processing unit 104 obtains coefficient data Wi corresponding to the class indicated by the class code CL obtained by the class detection circuit 113 and the values of the parameters r and z determined by the parameter determination circuit 118 from the ROM 117. This is read and supplied to the estimated prediction calculation circuit 121. By storing the coefficient data Wi itself in the ROM 120 in this way, it is possible to save the labor of calculation.

  In the embodiment described above, attention is paid to the parameter r for determining the resolution and the parameter z for determining the noise removal degree. However, the parameters for determining the image quality of the HD signal are limited to these parameters r and z. It is not something. Further, the number of parameters is not limited to two, and one or three or more parameters can be considered. For example, in the case of three, in addition to the parameter z that determines the degree of noise removal, a parameter h that determines the resolution in the horizontal direction and a parameter v that determines the resolution in the vertical direction are conceivable.

  Moreover, although the case where the information signal is an image signal has been described in the above embodiment, the present invention is not limited to this. For example, the present invention can be similarly applied when the information signal is an audio signal.

  The present invention extracts a feature amount of a target position in the second information signal based on information data of the first information signal located around the target position in the second information signal, Information on the position of interest in the second information signal is generated so that the quality of the output corresponding to the position of interest is the quality corresponding to the extracted feature quantity, and the quality of the output by the second information signal is For example, it can be applied to the use of obtaining an HD signal from an SD signal by a resolution creation technique.

It is a block diagram which shows the structure of the television receiver as embodiment. It is a figure which shows the pixel positional relationship of a 525i signal and a 1050i signal. It is a figure which shows an example of a class tap, a prediction tap, etc. It is a figure which shows the relationship between a pixel value and a luminance value. It is a figure which shows the example of a correspondence of a feature-value and a parameter value. It is a figure which shows the example of a correspondence of the feature-value and the value of a parameter. It is a figure which shows the phase shift (odd field) from the center prediction tap of 4 pixels in the unit pixel block of HD signal (1050i signal). It is a figure which shows the phase shift (even field) from the center prediction tap of 4 pixels in the unit pixel block of HD signal (1050i signal). It is a figure for demonstrating the production | generation method of coefficient seed data. It is a block diagram which shows the structure of a coefficient seed data generation apparatus. It is a block diagram which shows the structure of the image signal processing apparatus for implement | achieving by software. It is a flowchart which shows the procedure of an image signal process. It is a flowchart which shows the procedure of coefficient seed data generation processing. It is a figure for demonstrating the color space as a feature-value.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Television receiver, 101 ... Reception antenna, 102 ... Tuner part, 103 ... Buffer memory, 104 ... Image signal processing part, 105 ... Display part, 111 ... 1st 1 tap selection circuit, 112 ... second tap selection circuit, 113 ... third tap selection circuit, 114 ... spatial class detection circuit, 115 ... motion class detection circuit, 116 ... Class synthesis circuit, 117 ... feature amount extraction circuit, 118 ... parameter determination circuit, 119 ... coefficient generation circuit, 120 ... ROM, 121 ... estimated prediction calculation circuit, 122 ... post-processing Circuit, 150... Coefficient seed data generation device, 300... Image signal processing device

Claims (16)

An information signal processing device for converting a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data,
Based on the first information signal, information data located around the target position in the second information signal is selected, and based on the selected information data, the feature amount of the target position in the second information signal Feature amount extraction means for extracting
The information data of the target position in the second information signal is set so that the quality of the output corresponding to the target position in the second information signal is the quality corresponding to the feature amount extracted by the feature amount extraction means. An information signal processing device comprising: information data generating means for generating. Based on the feature quantity extracted by the feature quantity extraction means, further comprising parameter determination means for determining a parameter value indicating the quality of output by the second information signal,
2. The information signal processing according to claim 1, wherein the information data generation unit generates information data of a position of interest in the second information signal based on a parameter value determined by the parameter determination unit. apparatus. The information data generating means includes
Coefficient data generating means for generating coefficient data used in the estimation formula corresponding to the parameter value determined by the parameter determining means;
First data selection means for selecting a plurality of first information data located around the position of interest in the second information signal based on the first information signal;
Information on the position of interest in the second information signal based on the estimation formula using the plurality of first information data selected by the first data selection means and the coefficient data generated by the coefficient data generation means. The information signal processing apparatus according to claim 2, further comprising: an arithmetic unit that calculates data. The coefficient data generating means is
Storage means for generating coefficient data used in the estimation formula, storing coefficient seed data that is coefficient data of the generation formula including the parameter;
Using the coefficient seed data stored in the storage means and the parameter value determined by the parameter determination means, the coefficient data used in the estimation expression corresponding to the parameter value is generated based on the generation expression. The information signal processing apparatus according to claim 3, further comprising: a coefficient generation unit that performs processing. Second data selection means for selecting a plurality of second information data located around the position of interest in the second information signal based on the first information signal;
Class detection means for detecting a class to which the pixel data of the target position in the second information signal belongs based on the plurality of second information data selected by the second data selection means;
The coefficient data generation means generates coefficient data used in the estimation formula corresponding to the parameter value determined by the parameter determination means and the class detected by the class detection means. An information signal processing apparatus according to 1. The information signal is an image signal,
The information signal processing apparatus according to claim 2, wherein the value of the parameter indicates a resolution of an image or a noise removal degree based on the second information signal. The feature amount extraction means includes:
The information according to claim 1, wherein single information data located around a target position in the second information signal is selected, and a value of the single information data is extracted as the feature amount. Signal processing device. The feature amount extraction means includes:
The plurality of pieces of information data located around the position of interest in the second information signal are selected, and an average value of the plurality of pieces of information data is extracted as the feature amount. Information signal processing device. The feature amount extraction means includes:
Information data in the output means for selecting single information data located around the position of interest in the second information signal and obtaining the value of the single information data as an output by the second information signal The information signal processing apparatus according to claim 1, wherein the information value is converted into an output value based on a correspondence relationship between the value and the output value, and an output value obtained by the conversion is extracted as the feature amount. The information signal is an image signal,
The feature amount extraction unit extracts, as the feature amount, a luminance value as the output value obtained by converting a value of single pixel data as the single information data. 9. The information signal processing device according to 9. The feature amount extraction means includes:
The value of the information data in the output means for selecting the plurality of information data located around the position of interest in the second information signal and obtaining the value of the plurality of information data by the output of the second information signal 2. The information signal according to claim 1, wherein the information signal is converted into an output value based on a correspondence relationship between the output value and the output value, and an average value of a plurality of output values obtained by the conversion is extracted as the feature amount. Processing equipment. The information signal is an image signal,
The feature amount extracting means extracts, as the feature amount, an average value of a plurality of luminance values as the output value obtained by converting values of a plurality of pixel data as the plurality of information data. The information signal processing apparatus according to claim 11. An information signal processing method for converting a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data,
Based on the first information signal, information data located around the target position in the second information signal is selected, and based on the selected information data, the feature amount of the target position in the second information signal A feature extraction step for extracting
The information data of the target position in the second information signal is set so that the quality of the output corresponding to the target position in the second information signal becomes the quality corresponding to the feature amount extracted in the feature amount extraction step. An information signal processing method comprising: generating an information data step. A parameter determining step of determining a value of a parameter indicating the quality of output by the second information signal based on the feature amount extracted in the feature amount extraction step;
14. The information signal processing according to claim 13, wherein in the information data generation step, information data of a position of interest in the second information signal is generated based on the parameter value determined in the parameter determination step. Method. In order to convert a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data,
Based on the first information signal, information data located around the target position in the second information signal is selected, and based on the selected information data, the feature amount of the target position in the second information signal A feature extraction step for extracting
The information data of the target position in the second information signal is set so that the quality of the output corresponding to the target position in the second information signal becomes the quality corresponding to the feature amount extracted in the feature amount extraction step. A program for causing a computer to execute an information signal processing method comprising: an information data generation step to generate. In order to convert a first information signal composed of a plurality of information data into a second information signal composed of a plurality of information data,
Based on the first information signal, information data located around the target position in the second information signal is selected, and based on the selected information data, the feature amount of the target position in the second information signal A feature extraction step for extracting
The information data of the target position in the second information signal is set so that the quality of the output corresponding to the target position in the second information signal becomes the quality corresponding to the feature amount extracted in the feature amount extraction step. A computer-readable medium having recorded thereon a program for causing a computer to execute an information signal processing method comprising: an information data generation step to generate.

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