JP2009044417A - Image discrimination device, image discrimination method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image discrimination device, an image discrimination method, and a program, which discriminates an image without reference to by what upconverting system the image is upconverted. <P>SOLUTION: The image discrimination device includes a discrimination disturbance area excluding unit which detects a discrimination disturbance area as an disturbance to a discrimination on an image based upon an input image signal and outputs image signals corresponding to areas other than the discrimination disturbance area; a first frequency band signal detecting unit which detects signals of a plurality of frequency bands from the image signal output from the discrimination disturbance area excluding unit; a first average value calculating unit which calculates average values of characteristic values corresponding to amplitudes by the signals of the plurality of frequency bands detected by the first frequency band signal detecting unit; a first relative value calculating unit which calculates relative values of other average values to one average value among the average values calculated by the plurality of frequency bands; and a first image discrimination unit which discriminates the image, based upon the calculated relative values. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image determination device, an image determination method, and a program.

  In recent years, with the start of digital broadcasting, high-definition HD (High Definition) resolution image signals are transmitted from broadcast stations and the like. However, the image signals transmitted from broadcasting stations are not all HD resolution image signals, but SD (Standard Definition) resolution image signals used in conventional analog broadcasting are up-converted to HD resolution. In some cases, a pseudo HD resolution image signal is included.

  Known methods for up-converting an SD resolution image to an HD resolution image include a side panel method, a top and bottom crop method, and a stretch method.

  Generally, a pseudo HD resolution image obtained by up-converting an SD resolution image into an HD resolution image is inferior in terms of image quality as compared with a pure HD resolution image. Image correction such as enhancing the contour of the image using (Image Enhancer) is required.

  Under such circumstances, a technique has been developed for determining whether an image signal is an image obtained by up-converting an SD resolution image into an HD resolution image.

  An example of a technique for determining an image by detecting a side panel is Patent Document 1. Further, as a technique for determining an image by calculating average luminance in addition to detection of a side panel, for example, Patent Document 2 can be cited.

JP-A-2005-65195 JP-A-2005-26814

  However, the above-described technique for detecting an image by detecting a side panel requires that the signal of the side panel as an invalid area is only a signal equal to or less than a predetermined threshold. Therefore, the above-described technique for detecting an image by detecting a side panel is a case where a side panel signal added to an image obtained by up-converting an SD resolution image to an HD resolution image is a signal equal to or lower than a predetermined threshold. Only an image can be determined.

  In addition, the method of up-converting an SD resolution image to an HD resolution image is not only a side panel method but also a top-and-bottom crop method, a stretch method, etc., which do not include a side panel as an invalid area. There is. Therefore, the above-described technique for detecting an image by detecting a side panel cannot determine an image when the image signal does not include the side panel.

  In addition to the side panel detection described above, the technique for calculating the average luminance and determining the image is also based on the detection of the side panel. Therefore, if the side signal is not included in the image signal, the image Judgment cannot be made.

  Therefore, a conventional technique (conventional image determination technique) for determining whether an image indicated by an image signal is an image obtained by up-converting an SD resolution image into an HD resolution image is performed under certain conditions. Only a limited number of images can be determined.

  Accordingly, the present invention has been made in view of the above problems, and an object of the present invention is to determine an image regardless of the up-conversion method by which the image is up-converted. It is another object of the present invention to provide a new and improved image determination device, image determination method, and program.

  In order to achieve the above object, according to the first aspect of the present invention, a determination disturbing area that hinders image determination is detected based on an input image signal that is input, and an area other than the determination disturbing area is detected. A determination interference region exclusion unit that outputs a corresponding image signal, a first frequency band signal detection unit that detects signals in a plurality of frequency bands from the image signal output from the determination interference region exclusion unit, and the first A first average value calculation unit that calculates an average value of characteristic values corresponding to amplitude for each of signals in a plurality of frequency bands detected by the frequency band signal detection unit, and the above-described calculation for each of the plurality of frequency bands Of the average values, a first relative value calculation unit that calculates a relative value of another average value with respect to one of the average values, and a first image determination unit that determines an image based on the calculated relative value An image determination device comprising It is.

  The image determination apparatus includes a determination interference region exclusion unit, a first frequency band signal detection unit, a first average value calculation unit, a first relative value calculation unit, and a first image determination unit. be able to. For example, the determination interference area exclusion unit can detect a determination interference area that hinders determination of an image based on an input image signal that is input, and can output an image signal corresponding to an area other than the determination interference area. The first frequency band signal detection unit can detect signals in a plurality of frequency bands from the image signal, for example, by filtering the image signal for each pixel. The first average value calculation unit can calculate an average value of characteristic values corresponding to amplitude for each signal in a plurality of frequency bands. The 1st relative value calculation part can calculate the relative value of the other average value with respect to one average value among the average values for every frequency band. Here, the lower limit of the frequency in the frequency band derived from the one average value can be set lower than the lower limit of the frequency in the frequency band derived from the other average value, for example. The first image determination unit can determine an image based on the relative value calculated by the first relative value calculation unit. With this configuration, the image can be determined regardless of the up-conversion method of the image.

  In addition, the determination interference area exclusion unit includes a high-definition computer graphics area detection unit that detects a high-definition computer graphics area based on the input image signal, and a detection result in the high-definition computer graphics area detection unit. Accordingly, a non-high-definition computer graphics area detection unit that detects an area other than the high-definition computer graphics area and outputs the image signal may be provided.

  With this configuration, it is possible to output an image signal from which a high-definition computer graphics area image signal serving as a determination disturbance area that hinders image determination is excluded.

  The high-definition computer graphics area detection unit includes a second frequency band signal detection unit that detects signals in a plurality of frequency bands from the input image signal, and a plurality of detections detected by the second frequency band signal detection unit. Based on the first characteristic value calculation unit that calculates a characteristic value corresponding to the amplitude and the characteristic value calculated by the first characteristic value calculation unit for each signal in the frequency band, the characteristic value is the same level A flat area detecting unit that detects the flat area of each pixel, an edge area detecting unit that detects the edge area in units of pixels based on the characteristic values calculated by the first characteristic value calculating unit, and You may provide the 1st disturbance area | region detection part which detects the said high-definition computer graphics area | region based on the said flat area | region and the said edge area | region.

  With this configuration, it is possible to detect a high-definition computer graphics area as a determination interference area that hinders image determination.

  The first disturbing area detecting unit detects a nested area in which pixels in the flat area exist between pixels in the edge area as the high-definition computer graphics area. And an overdetection area exclusion unit that excludes an overdetection area from the detected high-definition computer graphics area.

  With this configuration, it is possible to detect a high-definition computer graphics area as a determination interference area that hinders image determination.

  In addition, the first disturbing region detection unit includes a pixel number detection unit that detects the number of pixels in a nested region in which pixels in the flat region exist between pixels in the edge region, and an image indicated by the input image signal. And a second computer graphics area detecting unit for detecting a high-definition computer graphics area for each local area based on the number of pixels detected by the pixel number detecting unit. May be.

  With this configuration, it is possible to detect a high-definition computer graphics area as a determination interference area that hinders image determination.

  In addition, the determination interference region exclusion unit includes a block distortion region detection unit that detects a block distortion region based on the input image signal, and an area other than the block distortion region according to a detection result in the block distortion region detection unit. And a non-block distortion region detection unit that detects and outputs the image signal.

  With such a configuration, it is possible to output an image signal from which an image signal of a block distortion region as a determination interference region that hinders image determination is excluded.

  The block distortion region detection unit includes a third frequency band signal detection unit that detects a plurality of frequency band signals from the input image signal, and a plurality of frequency bands detected by the third frequency band signal detection unit. A second characteristic value calculation unit that calculates a characteristic value corresponding to an amplitude for each of the signals, a block boundary detection unit that detects a block boundary based on the input image signal, the detected block boundary, and the first A variation value calculation unit that calculates a variation value of the characteristic value for each block based on the one characteristic value calculated by the second characteristic value calculation unit; and a second characteristic value for each of the plurality of frequency bands A third average value calculation unit that calculates an average value of the characteristic values calculated by the calculation unit; and a second average value that detects the block distortion region based on the calculated variation value or the average value. A, and a harmful region detection unit.

  With this configuration, it is possible to detect a block distortion region as a determination interference region that hinders image determination.

  In addition, for each of the signals in the plurality of frequency bands detected by the first frequency band signal detection unit, the signal processing apparatus further includes a noise removal unit that removes the signal having the characteristic value less than a predetermined threshold, The unit may calculate an average value of the characteristic values from which noise is removed by the noise removing unit.

  With this configuration, the image can be determined more accurately.

  Further, the first relative value calculation unit is configured to calculate the average value calculated in a predetermined frequency band, and the average value calculated in a frequency band higher than the predetermined frequency band. Based on the above, the relative value may be calculated.

  With this configuration, the image can be determined regardless of the up-conversion method of the image.

  The lower limit frequency of the predetermined frequency band is lower than the theoretically effective upper limit frequency according to the up-conversion method for the Nyquist frequency of the image up-converted from the standard resolution image, The lower limit frequency of the frequency band may be higher than the upper limit of the theoretically effective frequency according to the up-conversion method for the Nyquist frequency of the image up-converted from the standard resolution image.

  With this configuration, the image can be determined regardless of the up-conversion method of the image.

  In order to achieve the above object, according to the second aspect of the present invention, a determination disturbance area detection unit that detects a determination disturbance area that hinders determination of an image based on an input image signal that is input, A fourth frequency band signal detection unit that detects a plurality of frequency band signals from the input image signal, and a characteristic corresponding to an amplitude for each of the plurality of frequency band signals detected by the fourth frequency band signal detection unit A fourth average value calculation unit for calculating an average value of the values, and a first value for calculating a relative value of the other average value with respect to the one average value among the average values calculated for the plurality of frequency bands. 2 relative value calculation unit and a second image determination unit that determines an image based on the calculated relative value, and the fourth frequency band signal detection unit includes the determination interference region detection unit described above. Depending on detection result of judgment interference area Image judging apparatus for changing the frequency band is provided.

  The image determination apparatus includes a determination interference region detection unit, a fourth frequency band signal detection unit, a fourth average value calculation unit, a second relative value calculation unit, and a second image determination unit. be able to. The determination disturbance area detection unit can detect a determination disturbance area that hinders image determination based on the input image signal that is input. For example, the fourth frequency band signal detection unit can detect signals in a plurality of frequency bands from the image signal by filtering the image signal for each pixel. Here, the 4th frequency band signal detection part can change the frequency band which filters an image signal according to the detection result of the judgment interference field in a judgment interference field detection part. The fourth average value calculation unit can calculate the average value of the characteristic values corresponding to the amplitude for each signal in a plurality of frequency bands. The second relative value calculation unit can calculate a relative value of another average value with respect to one average value among the average values of the plurality of frequency bands. Here, the lower limit of the frequency in the frequency band derived from the one average value can be set lower than the lower limit of the frequency in the frequency band derived from the other average value, for example. The second image determination unit can determine an image based on the relative value calculated by the second relative value calculation unit. With this configuration, the image can be determined regardless of the up-conversion method of the image.

  In order to achieve the above object, according to the third aspect of the present invention, a determination disturbing area that hinders image determination is detected based on an input image signal that is input, and a region other than the determination disturbing area is detected. Outputting an image signal corresponding to a region; detecting a signal of a plurality of frequency bands from the image signal; and detecting an average value of characteristic values corresponding to amplitude for each of the detected signals of the plurality of frequency bands A step of calculating a relative value of another average value with respect to one of the average values among the average values calculated for each of the plurality of frequency bands, and based on the calculated relative value And determining an image.

  By using such a method, it is possible to determine an image regardless of the up-conversion method used for the image.

  In order to achieve the above object, according to the fourth aspect of the present invention, a determination disturbing area that hinders image determination is detected based on an input image signal that is input, and a region other than the determination disturbing area is detected. Outputting an image signal corresponding to a region; detecting a signal in a plurality of frequency bands from the image signal; and calculating an average value of characteristic values corresponding to the amplitude for each of the detected signals in the plurality of frequency bands. A step of calculating a relative value of another average value with respect to one of the average values calculated for each of the plurality of frequency bands, and determining an image based on the calculated relative value A program for causing a computer to execute the step of performing is provided.

  With such a program, the image can be determined regardless of the up-conversion method of the image.

  According to the present invention, it is possible to determine an image regardless of which up-conversion method is used for the image.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In the present specification and drawings, components having substantially the same functional configuration are denoted by the same reference numerals, and redundant description is omitted.

(Principle of image judgment)
First, the principle of image determination in the embodiment of the present invention will be described.

  FIG. 1 is an explanatory diagram showing an HD resolution image and an image obtained by up-converting an SD resolution image. Here, FIG. 1A shows an HD resolution image. 1B shows an SD resolution image, and FIG. 1C shows an image obtained by up-converting the SD resolution image (hereinafter referred to as “pseudo HD resolution image”). Yes.

  Also, as shown in FIG. 1C, a side panel as an invalid area is not always added to a pseudo HD resolution image. Therefore, the conventional image determination technique cannot determine a pseudo HD resolution image that does not include a side panel as shown in FIG. Therefore, in the embodiment according to the present invention, in order to discriminate between an HD resolution image and a pseudo HD resolution image, a difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image is used.

  FIG. 2 is an explanatory diagram for explaining the difference in frequency amplitude characteristics between the HD resolution image shown in FIG. 1A and the pseudo HD resolution image shown in FIG. FIG. 2 shows the relationship between frequency and amplitude in an image, with the normalized angular frequency on the horizontal axis and the power spectrum of the amplitude on the vertical axis.

  Referring to FIG. 2, the HD resolution image shown in FIG. 1 (a) and the pseudo HD resolution image shown in FIG. 1 (c) have a low frequency band in FIG. ”)), It can be seen that the amplitude of the signal is attenuated as the frequency is increased and the signal is increased. Here, the frequency amplitude characteristic in which the amplitude is large in the low frequency band as shown in FIG. 2 and the amplitude is attenuated as the frequency is increased is established for a general image such as a natural image.

  Here, when the HD resolution image signal and the pseudo HD resolution image signal are compared based on FIG. 2, the signal is similarly distributed in the low frequency band, but the amplitude attenuation rate is I can see that they are different. That is, in a band having a frequency higher than the low frequency band in FIG. 2 (hereinafter referred to as “middle frequency band”), the signal present in the area A in FIG. 2 is mainly an HD resolution image signal. There are very few pseudo HD resolution image signals. Therefore, the amplitude attenuation rate is larger in the pseudo HD resolution image than in the HD resolution image.

  Further, in a region where the frequency is higher than the middle frequency band in FIG. 2 (hereinafter referred to as “high frequency band”), the pseudo HD resolution image signal is hardly distributed, and the HD resolution image is not distributed. The difference is that the signal is distributed. Note that the frequency amplitude characteristics shown in FIG. 2 described above are not limited to the images shown in FIGS. 1A and 1C, and almost all the images have the same tendency.

  Therefore, in the embodiment according to the present invention, paying attention to the difference in the attenuation rate of the amplitude between the HD resolution image and the pseudo HD resolution image, the index (hereinafter referred to as “HD degree”) shown in Equation 1 is used. Used for judgment.

HD degree = (| average value of characteristic value corresponding to amplitude in frequency band 2) / (| average value of characteristic value corresponding to amplitude in frequency band 1)
... (Formula 1)

  The lower limit frequency of frequency band 1 in Equation 1 is set to a frequency lower than the lower limit frequency of frequency band 2. Therefore, from the frequency amplitude characteristic shown in FIG. 2, the HD degree takes a value of 0 ≦ HD degree <1. Here, the HD degree becomes 0 (zero) when the characteristic value corresponding to the amplitude (hereinafter referred to as “amplitude characteristic value”) does not exist in the frequency band 2.

  Here, the amplitude characteristic value may be the amplitude itself or an amplitude power spectrum. Needless to say, the amplitude characteristic value is not limited to the above. Moreover, although the average value shown in Numerical formula 1 can be calculated | required by an arithmetic mean, it is not restricted to the calculation method which concerns, For example, it is good also as a geometric average and can also be set as the weighted average which carried out predetermined weighting.

  In Formula 1, the HD degree is calculated based on the average value of the “absolute value of the amplitude characteristic value” in order to obtain the HD degree more accurately. It goes without saying that the HD degree can be calculated based on the “previous amplitude characteristic value”.

  Since the HD degree is a relative value between the average value of the amplitude characteristic values in the frequency band 1 and the average value of the amplitude characteristic values in the frequency band 2, the HD resolution image and the pseudo HD resolution shown in FIG. The difference in attenuation rate from the image can be expressed. Therefore, the higher the degree of HD of the image to be determined is closer to 0 (zero), the higher the probability that the image to be determined is a pseudo HD resolution image. As the value closer to 1 is taken, it can be said that the image to be judged is an HD resolution image.

(Outline of judgment processing)
The image determination apparatus according to the embodiment of the present invention determines whether the image indicated by the image signal is an HD resolution image or a pseudo HD resolution image by using the above-described image determination principle. Can do. However, for example, when an additional image such as a telop is superimposed on an image indicated by an image signal transmitted from a broadcasting station or the like, an accurate determination result cannot be obtained due to the additional image. (That is, erroneous determination occurs).

[Examples of judgment disturbance factors that may cause erroneous judgment]
FIG. 3 is an explanatory diagram for explaining an example of a determination disturbing factor that may cause an erroneous determination in the image determination apparatus according to the embodiment of the present invention. As shown in FIG. 3, the image indicated by the image signal may be, for example, an image in which high-definition computer graphics (hereinafter referred to as “CG”) such as time display and telop are superimposed on the landscape. is there. Here, since the “high-definition CG region” corresponding to the time display and the telop superimposed on the landscape shown in FIG. 3 is a high-definition HD resolution image region, the relationship between the frequency and the amplitude is shown in FIG. This is the same as the relationship indicated by (a) (see FIG. 2).

  Therefore, for example, even if the “non-CG area” corresponding to the landscape portion shown in FIG. 3 is an SD resolution image area, the above-described image determination principle is affected by the influence of the “high-definition CG area”. When the image determination apparatus to be used performs image determination on the entire image, it may be determined that the image is an HD resolution image (an erroneous determination occurs).

  In addition, the determination disturbing factor that may cause an erroneous determination in the image determination apparatus using the above-described image determination principle is not limited to the above (1) high-definition CG superimposed on the image. For example, (2) MPEG compression, Block distortion in an image compressed in a predetermined format such as JPEG compression, (3) Dot disturbance that may occur in the contour portion when the luminance signal and color signal cannot be separated accurately, and (4) Mosaic superimposed on the image (Mosaic) images, (5) side panels added by the side panel method, and the like.

[Overview of judgment processing]
Therefore, an outline of processing in the image determination apparatus according to the embodiment of the present invention that can perform image determination on an image having a determination interference factor that may cause erroneous determination as shown in FIG.

[Overview of the first determination process]
The image determination apparatus according to the embodiment of the present invention performs image determination by the following processes (A-1) to (A-3), for example.

(A-1) Detection of Determination Interference Factor The image determination apparatus according to the embodiment of the present invention detects the determination interference factor as shown in the above (1) to (5) based on an input image signal. A method for detecting a determination interference factor in the image determination apparatus according to the embodiment of the present invention will be described later.

(A-2) Exclusion of Determination Interference Factor The image determination apparatus according to the embodiment of the present invention excludes the detected determination interference factor from the image signal.

(A-3) Image Determination The image determination apparatus according to the embodiment of the present invention determines an image based on an image signal from which a determination interference factor is excluded.

[Overview of second determination process]
The image determination apparatus according to the embodiment of the present invention can also determine an image by the following processes (B-1) to (B-3).

(B-1) Detection of Determination Interference Factor The image determination apparatus according to the embodiment of the present invention detects the determination interference factor as shown in the above (1) to (5) based on an input image signal.

(B-2) Change of frequency band for calculating relative value The image determination apparatus according to the embodiment of the present invention changes the frequency band for calculating the relative value according to the detected determination interference factor. By changing the frequency band for calculating the relative value according to the determination disturbance factor, the image determination apparatus according to the embodiment of the present invention calculates the relative value from which the determination disturbance factor is effectively removed, and the image Judgment can be made.

(B-3) Image Determination An image determination apparatus according to an embodiment of the present invention performs image determination.

  The image determination apparatus according to the embodiment of the present invention performs, for example, the processing shown in (A-1) to (A-3) or (B-1) to (B-3), thereby Regardless of which up-conversion method is used for up-conversion, image determination can be performed.

  Hereinafter, an image determination apparatus according to an embodiment of the present invention using the above-described image determination principle will be described in more detail. In the following description, an image signal is input to the image determination apparatus according to the embodiment of the present invention. However, the image signal input to the image determination apparatus may indicate a still image. Alternatively, it may be a moving image (so-called video).

  Further, the image signal input to the image determination apparatus according to the embodiment of the present invention may be a digital signal used in digital broadcasting, for example, and is not limited to the above, and is used in analog broadcasting, for example. It can also be an analog signal. Note that the image signal input to the image determination apparatus according to the embodiment of the present invention can be transmitted from a broadcasting station and received by the image determination apparatus, but is not limited thereto. For example, the image signal input to the image determination device according to the embodiment of the present invention may be transmitted from an external device via a network such as a LAN (Local Area Network) and received by the image determination device. Alternatively, the image determination device may read a video file or an image file held in a storage unit included in the image determination device.

(First embodiment)
FIG. 4 is a block diagram showing the image determination apparatus 100 according to the first embodiment of the present invention. Here, the image determination apparatus 100 can determine an image by the process shown in the outline of the first determination process described above.

  Referring to FIG. 4, the image determination device 100 according to the first embodiment includes a determination interference region exclusion unit 102, a frequency band signal detection unit 104, a noise removal unit 106, an average value calculation unit 108, and a relative value. A calculation unit 110, a sample number reliability setting unit 112, an average value reliability setting unit 114, a reliability setting unit 116, and an image determination unit 118 are provided.

  In addition, the image determination apparatus 100 includes, for example, a control unit (not shown) configured by an MPU (Micro Processing Unit) or the like that can control the entire image determination apparatus 100, and programs and calculation parameters used by the control unit. ROM (Read Only Memory; not shown) in which data for control such as the above are recorded, RAM (Random Access Memory; not shown) for temporarily storing a program executed by the control unit, and the image determination apparatus 100 make the determination. A storage unit (not shown) that can store an image to be performed, a receiving unit (not shown) that receives an image signal transmitted from a broadcasting station, an operation unit (not shown) that can be operated by a user, and the like are provided. Also good. For example, the image determination apparatus 100 can connect the above constituent elements by a bus as a data transmission path. Here, as the storage unit (not shown), for example, a magnetic recording medium such as a hard disk, a non-volatile memory such as a flash memory, a magneto-optical disk ) Etc., but is not limited to the above. In addition, examples of the operation unit (not shown) include operation input devices such as a keyboard and a mouse, buttons, direction keys, and combinations thereof, but are not limited thereto. Absent.

The determination interference area exclusion unit 102 can detect an area having a determination interference factor that may cause an erroneous determination, and output an image signal from which an image signal of the area having the determination interference factor is excluded.
Hereinafter, first to sixth configuration examples of the determination interference area excluding unit 102 will be described.

[First Configuration Example of Determination Interference Area Exclusion Unit 102: Exclusion of High-Definition CG Area]
First, as a first configuration example of the determination disturbance area exclusion unit 102, a configuration corresponding to the determination disturbance factor shown in (1) above, that is, a high-definition CG such as a time display and a telop as shown in FIG. 3 is included. The structure which can exclude a high-definition CG area | region is shown.

[Exclusion Means of First Configuration Example of Determination Interference Area Exclusion Unit 102]
FIG. 5 is an explanatory diagram for explaining the difference in frequency amplitude characteristics between the image signal in the non-CG area shown in FIG. 3 and the image signal in the high-definition CG area shown in FIG. FIG. 5 shows the relationship between frequency and amplitude in an image, with the normalized angular frequency on the horizontal axis and the power spectrum of the amplitude on the vertical axis.

  Referring to FIG. 5, the non-CG region image signal shown in FIG. 3 and the high definition CG region image signal shown in FIG. 3 are higher in the high definition CG region image signal in the frequency band higher than frequency a. It can be seen that the signal component has a larger amplitude than the image signal in the non-high definition CG region. Therefore, the determination interference region exclusion unit 102 according to the first configuration example uses the difference between the image signal of the non-CG region and the image signal of the high definition CG region illustrated in FIG. Exclude image signals in the CG area.

[Determination Interference Area Exclusion Unit 102 According to First Configuration Example]
FIG. 6 is a block diagram illustrating a first configuration example of the determination interference area exclusion unit 102 according to the first embodiment of the present invention. Referring to FIG. 6, the determination interference region exclusion unit 102 according to the first configuration example includes a high-definition CG region detection unit 200 and a non-high-definition CG region detection unit 202.

  The high-definition CG region detection unit 200 includes a frequency band signal detection unit 204, a characteristic value calculation unit 206, a flat region detection unit 208, an edge region detection unit 210, and an interference region detection unit 212, and is input. Based on the image signal, for example, a high-definition CG region as shown in FIG. 3 can be detected.

<Configuration of High-Definition CG Area Detection Unit 200>
The frequency band signal detection unit 204 includes a first frequency band signal detection unit 220 and a second frequency band signal detection unit 222, and performs filtering of an input image signal. The first frequency band signal detection unit 220 and the second frequency band signal detection unit 222 perform processing for each pixel, for example, pass only an image signal having a frequency equal to or higher than the cutoff frequency, and an image signal having a frequency lower than the cutoff frequency. Can be configured with a high-pass filter (hereinafter referred to as “HPF”).

  The first frequency band signal detection unit 220 is, for example, a broadband HPF that passes an image signal up-converted from an SD resolution image and an HD resolution image signal and does not pass a DC (Direct Current) component. Composed.

  The second frequency band signal detection unit 222 is configured by, for example, an HPF that passes only a frequency band higher than the upper limit of the theoretically effective frequency with respect to the Nyquist frequency in an image up-converted from an SD resolution image. .

  The first frequency band signal detection unit 220 and the second frequency band signal detection unit 222 are not limited to the HPF, and, for example, pass only an image signal in a specific frequency band and attenuate image signals in other bands. A band-pass filter (Band-Pass Filter; hereinafter referred to as “BPF”) may also be used.

The characteristic value calculation unit 206 includes a first characteristic value calculation unit 224 and a second characteristic value calculation unit 226.
Based on the filtered image signal output from the frequency band signal detection unit 204, an amplitude characteristic value for each pixel is calculated. More specifically, the first characteristic value calculation unit 224 calculates an amplitude characteristic value based on the image signal output from the first frequency band signal detection unit 220, and the second characteristic value calculation unit 226 The amplitude characteristic value is calculated based on the image signal output from the two frequency band signal detection unit 222.

  The first characteristic value calculation unit 224 and the second characteristic value calculation unit 226 can calculate the amplitude characteristic value by, for example, calculating the absolute value of the filtered image signal, but is not limited thereto.

  Based on the amplitude characteristic value output from the first characteristic value calculation unit 224, the flat area detection unit 208 removes the amplitude characteristic value of a portion corresponding to a so-called pattern, and corresponds to a flat region having the same amplitude characteristic value. By outputting an image signal to be detected, the flat area can be detected in units of pixels.

  Here, the process in the flat region detection unit 208 can be performed by, for example, a threshold process that removes an amplitude characteristic value having an amplitude characteristic value equal to or greater than a predetermined threshold. The information on the predetermined threshold value may be stored in the storage unit, for example, in which the flat area detection unit 208 includes a storage unit. Examples of the storage unit included in the flat area detection unit 208 include EEPROM (Electronically Erasable and Programmable Read Only Memory), flash memory, MRAM (Magnetoresistive Random Access Memory), FeRAM (Ferroelectric Random Access Memory), and PRAM (Phase change Random Access). Non-volatile memory such as (Memory) is mentioned, but is not limited to the above. Needless to say, the predetermined threshold value may be stored in, for example, a storage unit (not shown) of the image determination apparatus 100, and the flat area detection unit 208 may appropriately read from the storage unit (not shown). Yes.

  The flat area detecting means in the flat area detecting unit 208 is not limited to the above. For example, an image flat area detecting unit (not shown) is separately provided in the image processing apparatus according to the first embodiment, and the image flattening is performed. A flat region may be set based on the detection result of the region detection unit.

  The edge area detection unit 210 detects an edge area by detecting an image signal corresponding to an edge of HD resolution based on the amplitude characteristic value output from the second characteristic value calculation unit 226 and outputting the image signal in units of pixels. be able to.

  Here, the processing in the edge region detection unit 210 can be performed, for example, by threshold processing that outputs an amplitude characteristic value having an amplitude characteristic value equal to or greater than a predetermined threshold. For example, the edge area detection unit 210 may include a storage unit, and the predetermined threshold information may be stored in the storage unit. Examples of the storage unit included in the edge region detection unit 210 include, but are not limited to, a non-volatile memory such as an EEPROM or a flash memory. It should be noted that the predetermined threshold value is stored in, for example, a storage unit (not shown) of the image determination apparatus 100, and the edge region detection unit 210 may appropriately read from the storage unit (not shown). Yes.

  Note that the edge region detection means in the edge region detection unit 210 is not limited to the above. For example, an image edge region detection unit (not shown) is separately provided in the image processing apparatus according to the first embodiment, and the image edge is detected. An edge region may be set based on the detection result of the region detection unit.

  Based on the flat area detected by the flat area detection unit 208 and the edge area detected by the edge area detection unit 210, the interference area detection unit 212 detects a high-definition CG region that becomes an interference factor. Hereinafter, a high-definition CG region detection unit in the interference region detection unit 212 will be described.

[1] First Detection Means in Blocking Area Detection Unit 212 FIG. 7 is a block diagram showing a first configuration example of the blocking area detection unit 212 according to the first embodiment of the present invention, and FIG. It is explanatory drawing for demonstrating the 1st detection means in the disturbance area | region detection part 212 which concerns on the 1st Embodiment of this invention.

  Referring to FIG. 7, the disturbing region detection unit 212 according to the first configuration example includes a first CG region detection unit 228 and an overdetection region exclusion unit 230.

  The first CG region detection unit 228 detects a high-definition CG region based on the flat region detected by the flat region detection unit 208 and the edge region detected by the edge region detection unit 210.

  Here, as shown in FIG. 8, the first CG region detecting unit 228 is a region where the region surrounded by the edge is a flat region detected by the flat region detecting unit 208 (the edge and the flat region are nested. (Related region) can be detected as a high-definition CG region. Note that the first CG region detection unit 228 may detect the region as a high-definition CG region, for example, when most of the region surrounded by the edge is a flat region in consideration of the influence of noise.

  The overdetection region exclusion unit 230 determines an overdetected region from the high definition CG region detected by the first CG region detection unit 228, and excludes the overdetection region from the high definition CG region. .

  Here, the over-detection region exclusion unit 230 is detected by the first CG region detection unit 228, for example, by threshold processing using an upper limit threshold and a lower limit threshold with respect to a preset size of the high-definition CG region. An over-detected area can be determined from the high-definition CG area. Note that the information on the upper limit threshold and the lower limit threshold may be stored in the storage unit, for example, the overdetection area exclusion unit 230 may include a storage unit. Examples of the storage unit included in the overdetection area exclusion unit 230 include, but are not limited to, a nonvolatile memory such as an EEPROM or a flash memory. The upper limit threshold and the lower limit threshold may be fixed values defined in advance, or may be set as appropriate according to user input.

  Note that the method of determining an overdetected region in the overdetection region exclusion unit 230 is not limited to the above, and for example, an overdetected region can be determined based on information such as the shape of the region and the detection position. .

  The interference region detection unit 212 according to the first configuration example can detect the high-definition CG region by the configuration as described above.

[2] Second Detection Means in Interference Area Detection Unit 212 With the configuration shown in FIG. 7, the interfering area detection unit 212 can detect a high-definition CG area. The area detecting means is not limited to the above. Therefore, the second detection means in the interference area detection unit 212 will be described next.

  FIG. 9 is a block diagram showing a second configuration example of the disturbing area detecting unit 212 according to the first embodiment of the present invention, and FIG. 10 is a disturbing area detecting unit according to the first embodiment of the present invention. It is explanatory drawing for demonstrating the 2nd detection means in 212. FIG.

  Referring to FIG. 9, the interference region detection unit 212 according to the second configuration example includes a pixel number detection unit 232 and a second CG region detection unit 234.

  Similar to the first CG region detection unit 228 shown in FIG. 7, the pixel number detection unit 232 has a nested relationship between the edge and the flat region based on the detection results of the flat region detection unit 208 and the edge region detection unit 210. A certain region is detected, and the number of pixels in the nested relationship (hereinafter referred to as “detected pixel number”) is detected.

  As shown in FIG. 10, the second CG region detection unit 234 divides the entire image into a plurality of regions (hereinafter referred to as “local regions”), and based on the number of detected pixels detected by the pixel number detection unit 232. A high-definition CG area is detected for each local area. In addition, although the example which divided | segmented the local area | region into the grid pattern of equal areas was shown in FIG. 10, the local area | region which concerns on embodiment of this invention is not restricted to the example shown in FIG. For example, the local region according to the embodiment of the present invention may have a lattice shape with different areas, or may be divided into non-lattice shapes with different shapes and areas.

  Further, the second CG region detection unit 234 can detect the high-definition CG region by the method shown in FIG. 11, for example. FIG. 11 is a flowchart showing an example of a high-definition CG region detection method in the second CG region detection unit 234 according to the first embodiment of the present invention. Here, the detection method shown in FIG. 11 is performed for each local region.

  The second CG region detection unit 234 determines whether or not the number of detected pixels in one local region is larger than the first threshold (TH1) (S100; first determination). Here, the first threshold value is a threshold value set to directly determine whether the local region is a high-definition CG region. The first threshold value may be stored in the storage unit, for example, the second CG region detection unit 234 includes a storage unit. Examples of the storage unit included in the second CG region detection unit 234 include non-volatile memories such as an EEPROM and a flash memory, but are not limited thereto. Further, the first threshold value may be, for example, a fixed value defined in advance, or may be appropriately set according to user input.

  If it is determined in step S100 that the number of detected pixels in one local region is larger than the first threshold, the second CG region detecting unit 234 determines that the one local region is a high-definition CG region ( S108). And the 2nd CG area | region detection part 234 advances a process to the next local area | region.

  If it is determined in step S100 that the number of detected pixels in one local region is equal to or smaller than the first threshold, the second CG region detecting unit 234 determines that the number of detected pixels in one local region is the second. It is determined whether it is larger than the threshold value (TH2) (S102; second determination). Here, referring to FIG. 10, it can be seen that the number “9” of the high-definition CG exists across the local region C and the local region D. As described above, depending on how the local region is set, there is a possibility that the high-definition CG exists across a plurality of local regions. Therefore, the second CG region detection unit 234 performs the second step shown in step S102 in order to more accurately determine whether each local region is a high-definition CG region even in the case of FIG. Judgment is made. More specifically, the second determination can be said to be a determination for enumerating a region that includes a certain number of detected pixels as a detection candidate for a high-definition CG region. That is, the second threshold value is a threshold value set to detect a region that may include high-definition CG that exists across a plurality of local regions, as shown in FIG. Is a threshold value that is set to indirectly determine whether or not is a high-definition CG region. Further, the second threshold value can be a value smaller than the first threshold value. For example, the second threshold value may be stored in a storage unit included in the second CG region detection unit 234, but is not limited thereto. Further, the second threshold value may be a fixed value defined in advance as in the case of the first threshold value, or may be appropriately set according to user input.

  When it is determined in step S102 that the number of detected pixels in one local region is equal to or smaller than the second threshold, the second CG region detecting unit 234 determines that the one local region is a non-CG region ( S110). And the 2nd CG area | region detection part 234 advances a process to the next local area | region.

  If it is determined in step S102 that the number of detected pixels in one local region is larger than the second threshold, the second CG region detecting unit 234 determines a local region adjacent to the one local region. The result is confirmed (S104). Here, although not shown in FIG. 11, when the determination result of the adjacent local region cannot be confirmed in step S104, that is, when the determination of the adjacent local region has not been performed yet, the second CG region detection is performed. For example, the unit 234 can interrupt the process for the one local region and perform the detection process for the other local region.

  The second CG region detection unit 234 determines whether there is a high-definition CG region in the adjacent local region based on the result of the confirmation process in step S104 (S106; third determination).

  If it is determined in step S106 that there is a high-definition CG region in the adjacent local region, the second CG region detection unit 234 determines that the one local region is a high-definition CG region (S108). And the 2nd CG area | region detection part 234 advances a process to the next local area | region.

  If it is determined in step S106 that there is no high-definition CG region in the adjacent local region, the second CG region detection unit 234 determines that the one local region is a non-CG region (S110). And the 2nd CG area | region detection part 234 advances a process to the next local area | region.

  As described above, by performing the processing of steps S100 to S110 illustrated in FIG. 11, the second CG region detection unit 234 performs, for example, high-definition CG across a plurality of local regions as illustrated in FIG. Even if it exists, it is possible to determine whether each local region is a high-definition CG region based on the number of detected pixels for each local region.

  In addition, the second CG region detection unit 234 using the second detection unit can determine the high-definition CG region using two threshold values, the first threshold value and the second threshold value. Therefore, the second CG region detection unit 234 using the second detection means can detect the high-definition CG region more accurately even if there is a detection failure in the flat region detection unit 208 and / or the edge region detection unit 210, for example. Can be detected.

  The interference region detection unit 212 according to the second configuration example can detect the high-definition CG region with the above configuration.

[3] Third Detection Means in Interference Area Detecting Unit 212 The interfering area detecting unit 212 has a high-definition configuration as shown in FIG. 7 (first configuration example) and FIG. 9 (second configuration example), for example. Although the CG area can be detected, the high-definition CG area detection means in the disturbing area detection unit 212 is not limited to the above. For example, the interference region detection unit 212 has a high-definition CG region by a configuration (third configuration example) that combines the configuration shown in FIG. 7 (first configuration example) and the configuration shown in FIG. 9 (second configuration example). Can also be detected.

  FIG. 12 is a block diagram showing a third configuration example of the interference area detection unit 212 according to the first embodiment of the present invention. Referring to FIG. 12, the disturbance region detection unit 212 according to the third configuration example includes a first CG region detection unit 228, an overdetection region exclusion unit 230, a pixel number detection unit 232, and a second CG region detection unit. 234. Here, the first CG region detection unit 228 and the overdetection region exclusion unit 230 according to the third configuration example illustrated in FIG. 12 have functions and configurations similar to those of the first configuration example illustrated in FIG. it can. Further, the pixel number detection unit 232 and the second CG region detection unit 234 according to the third configuration example illustrated in FIG. 12 can have the same functions and configurations as those of the second configuration example illustrated in FIG.

  Therefore, when the disturbing region detection unit 212 according to the first embodiment of the present invention has the configuration shown in FIG. 12 (third configuration example), the high-definition CG region detection unit 200 includes, for example, an “edge region” Further, a high-definition CG region can be detected by a series of processes of “flat region detection → overdetection region exclusion processing → high-definition CG region pixel number detection for each local region → high-definition CG region determination processing for each local region”.

  As described above with reference to FIGS. 6 to 12, the high-definition CG region detection unit 200 can detect the high-definition CG region based on the input image signal.

  With reference to FIG. 6 again, the determination interference region exclusion unit 102 according to the first configuration example will be described. The non-high definition CG region detection unit 202 detects a region other than the high definition CG region, that is, a non-high definition CG region based on the high definition CG region detected by the high definition CG region detection unit 200. Here, in the non-high-definition CG area detected by the non-high-definition CG area detection unit 202, an image other than the high-definition CG, for example, a non-CG image or a standard resolution (SD resolution) CG image is up-converted. A CG image is included. Therefore, the image signal output from the non-high-definition CG region detection unit 202 is an image signal from which the image signal of the high-definition CG region that can be a determination interference factor is excluded.

  The determination interference region exclusion unit 102 according to the first configuration example can output, for example, an image signal from which an image signal of a high-definition CG region that can be a determination interference factor is excluded by the configuration illustrated in FIG.

  Note that the configuration of the determination interference area exclusion unit according to the first configuration example is not limited to the above. For example, the determination interference region exclusion unit according to the first configuration example includes only the non-high-definition CG region detection unit, and the high-definition CG region detection unit (not shown) separately included in the image processing apparatus according to the first embodiment. On the basis of the region information from the image signal, it is also possible to output an image signal from which the image signal of the high-definition CG region from which the determination interference region exclusion unit according to the first configuration example can be a determination interference factor is excluded.

[Second Configuration Example of Judgment Interference Area Exclusion Unit 102: Exclusion of Block Distortion Area]
As described above, the determination disturbance factor is not limited to the high-definition CG. Therefore, as a second configuration example of the determination interference area exclusion unit 102, a configuration corresponding to the determination interference factor shown in (2) above, that is, a block in an image compressed in a predetermined format such as MPEG compression or JPEG compression. A configuration capable of excluding a region where distortion has occurred will be described. Here, block distortion is a kind of noise mixed after up-conversion processing. The image determination apparatus 100 can reduce the possibility of erroneous determination due to the influence of noise by excluding an area where block distortion has occurred. Therefore, the image determination apparatus 100 can determine an image more accurately.

  Note that the image targeted by the determination disturbance area exclusion unit 102 according to the second configuration example is not limited to an MPEG compressed image or a JPEG compressed image, and block distortion such as an AVC compressed image may occur. It goes without saying that various images can be targeted. In the following, an example for an MPEG compressed image is shown.

[Exclusion Means of Second Configuration Example of Determination Interference Area Exclusion Unit 102]
FIG. 13 is an explanatory diagram for explaining a difference in frequency amplitude characteristics between a non-block distortion region in which block distortion has not occurred and a block distortion region in which block distortion has occurred. FIG. 13 shows the relationship between frequency and amplitude in an image, with the normalized angular frequency on the horizontal axis and the logarithm of the power spectrum of the amplitude on the vertical axis.

  Referring to FIG. 13, it can be seen that the image signal in the block distortion region has a larger signal component than the image signal in the non-block distortion region between the bands of frequency a and frequency b. Therefore, the judgment interference area exclusion unit 102 according to the second configuration example uses the difference between the image signal in the non-block distortion area and the image signal in the block distortion area shown in FIG. The image signal of the block distortion area in the processed image is excluded.

[Determination Interference Area Exclusion Unit 102 According to Second Configuration Example]
FIG. 14 is a block diagram illustrating a second configuration example of the determination interference area exclusion unit 102 according to the first embodiment of the present invention. Referring to FIG. 14, the determination interference region exclusion unit 102 according to the second configuration example includes a block distortion region detection unit 300 and a non-block distortion region detection unit 302.

  The block distortion region detection unit 300 includes a frequency band signal detection unit 304, a characteristic value calculation unit 306, a block boundary detection unit 308, a variation value calculation unit 310, an average value calculation unit 312, and an interference region detection unit 314. The block distortion region can be detected based on the input image signal.

<Configuration of Block Distortion Area Detection Unit 300>
The frequency band signal detection unit 304 includes a first frequency band signal detection unit 320 and a second frequency band signal detection unit 322, and performs filtering of an input image signal. For example, the first frequency band signal detection unit 320 and the second frequency band signal detection unit 322 perform processing for each pixel, pass only an image signal having a frequency equal to or higher than the cutoff frequency, and have an image signal having a frequency lower than the cutoff frequency. It can be composed of an HPF that attenuates.

  The first frequency band signal detection unit 320 is configured by, for example, a broadband HPF that allows an image signal up-converted from an SD resolution image to pass therethrough.

  The second frequency band signal detection unit 322 is configured by, for example, an HPF that passes a frequency band higher than the theoretically effective upper limit for the Nyquist frequency in an image upconverted from an SD resolution image.

  The first frequency band signal detection unit 320 and the second frequency band signal detection unit 322 are not limited to the HPF, and, for example, pass only an image signal in a specific frequency band and attenuate image signals in other bands. A BPF may be used.

The characteristic value calculation unit 306 includes a first characteristic value calculation unit 324 and a second characteristic value calculation unit 326.
Based on the filtered image signal output from the frequency band signal detection unit 304, an amplitude characteristic value for each pixel is calculated. More specifically, the first characteristic value calculation unit 324 calculates an amplitude characteristic value based on the image signal output from the first frequency band signal detection unit 320, and the second characteristic value calculation unit 326 An amplitude characteristic value is calculated based on the image signal output from the two frequency band signal detection unit 322.

  The first characteristic value calculation unit 324 and the second characteristic value calculation unit 326 can calculate the amplitude characteristic value by, for example, calculating the absolute value of the filtered image signal, but is not limited thereto.

  The block boundary detection unit 308 detects a block boundary in the MPEG compressed image based on the input image signal, and outputs block boundary information.

  The variation value calculation unit 310, based on the block boundary information output from the block boundary detection unit 308 and the amplitude characteristic value output from the first characteristic value calculation unit 324, varies the amplitude characteristic value in the pixels inside the block. Calculate the value. Here, the variation value is a value for evaluating variation in the amplitude characteristic value, and examples thereof include a variance value, a standard deviation value, and an average deviation value.

  The average value calculation unit 312 includes a first average value calculation unit 330 and a second average value calculation unit 332, and includes block boundary information output from the block boundary detection unit 308 and amplitude output from the characteristic value calculation unit 306. Based on the characteristic values, the average value of the amplitude characteristic values in the pixels inside the block and the average value of the amplitude characteristic values in the pixels at the block boundary are calculated.

  The first average value calculation unit 330 is based on the block boundary information output from the block boundary detection unit 308 and the amplitude characteristic value output from the first characteristic value calculation unit 324, and the amplitude characteristic value in the pixel at the block boundary part And an average value of amplitude characteristic values of pixels in the block are calculated.

  The second average value calculation unit 332 also determines the amplitude of the pixel at the block boundary portion based on the block boundary information output from the block boundary detection unit 308 and the amplitude characteristic value output from the second characteristic value calculation unit 326. The average value of the characteristic values and the average value of the amplitude characteristic values in the pixels inside the block are calculated.

  Here, the average value in the 1st average value calculation part 330 and the 2nd average value calculation part 332 can be calculated | required by an arithmetic mean, for example. Needless to say, the average value calculation method in the average value calculation unit 312 is not limited to the arithmetic average, and can be calculated by various methods such as a geometric average and a weighted average.

  The disturbing region detection unit 314 includes a first block strain region detection unit 334 and a second block strain region detection unit 336. In each of the first block strain region detection unit 334 and the second block strain region detection unit 336, a disturbing factor is provided. A block distortion region is detected.

  The first block distortion region detection unit 334 detects a block distortion region based on the variation value calculated by the variation value calculation unit 310.

  Here, the first block distortion area detection unit 334 can detect the block distortion area by, for example, threshold processing that determines block distortion when the variation value is equal to or less than a predetermined threshold. The detecting means is not limited to the above. The information on the predetermined threshold value may be stored in the storage unit, for example, by the interference region detection unit 314 (which may be included in the first block distortion region detection unit 334). As a memory | storage part with which the disturbance area | region detection part 314 is provided, non-volatile memories, such as EEPROM and flash memory, are mentioned, for example, It is not restricted above. Needless to say, the predetermined threshold value may be stored in, for example, a storage unit (not shown) of the image determination apparatus 100, and the disturbing area detection unit 314 may appropriately read from the storage unit (not shown). Yes.

  The second block distortion region detection unit 336 includes the average value of the amplitude characteristic value in the pixel at the block boundary calculated by the first average value calculation unit 330 and the second average value calculation unit 332 and the amplitude characteristic in the pixel inside the block. A block distortion region is detected based on the average value.

More specifically, the second block distortion region detection unit 336 uses, for example, the average values calculated by the first average value calculation unit 330 and the second average value calculation unit 332, respectively, and at least of the following conditions: A region satisfying one can be determined to be a block distortion region. And the 2nd block distortion area | region detection part 336 can detect a block distortion area | region by using a determination result.
<Condition 1>
{(Average value in the block calculated by the first average value calculation unit 330) / (Average value in the block boundary calculated by the first average value calculation unit 330)} <Threshold <Condition 2>
{(Average value inside block calculated by second average value calculation unit 332) / (average value at block boundary calculated by second average value calculation unit 332)} <threshold

  Here, the information on the predetermined threshold value may be stored in the storage unit, for example, by the interference region detection unit 314 (which may be included in the second block distortion region detection unit 336). It is not limited to the above.

  The disturbing area detection unit 314 can use the block distortion areas detected by the first block distortion area detection unit 334 and the second block distortion area detection unit 336, respectively, as the detected block distortion areas.

  With the configuration as described above, the block distortion area detection unit 300 can detect a block distortion area based on an input image signal.

  The non-block distortion region detection unit 302 detects a region other than the block distortion region, that is, a non-block distortion region based on the block distortion region detected by the block distortion region detection unit 300. Therefore, the image signal output from the non-block distortion region detection unit 302 is an image signal from which the image signal of the block distortion region that can be a determination disturbing factor is excluded. Even if the block distortion region detected by the first block distortion region detection unit 334 and the block distortion region detected by the second block distortion region detection unit 336 overlap, the non-block distortion region detection unit 302 A non-block distortion region can be detected by detecting areas other than the block distortion areas output from the 1-block distortion area detection unit 334 and the second block distortion area detection unit 336, respectively.

  The determination interference region exclusion unit 102 according to the second configuration example can output, for example, an image signal from which an image signal of a block distortion region that can be a determination interference factor is excluded by the configuration illustrated in FIG.

  Note that the configuration of the determination interference area exclusion unit according to the second configuration example is not limited to the above. For example, from the block distortion area | region detection part (not shown) with which the determination disturbance area exclusion part which concerns on a 2nd structural example is provided with only a non-block distortion area | region detection part, and the image processing apparatus which concerns on 1st Embodiment is provided separately. Based on the region information, it is also possible to output an image signal from which the image signal of the block distortion region that can be a determination interference factor is excluded by the determination interference region exclusion unit according to the second configuration example.

[Third Configuration Example of Judgment Interference Area Exclusion Unit 102: Exclusion of Dot Interference Area]
As described above, the determination interference factor is not limited to high-definition CG or block distortion. Then, next, as a third configuration example of the determination interference area exclusion unit 102, a configuration corresponding to the determination interference factor shown in the above (3), that is, a configuration capable of excluding an area where dot interference has occurred will be described. To do. Here, the dot interference is a kind of noise that can occur in the contour portion when the luminance signal and the color signal cannot be accurately separated. The image determination apparatus 100 can reduce the possibility of erroneous determination due to the influence of noise by excluding the area where dot interference has occurred. Therefore, the image determination apparatus 100 can determine an image more accurately.

[Exclusion Means of Third Configuration Example of Determination Interference Area Exclusion Unit 102]
FIG. 15 is an explanatory diagram for explaining a difference in frequency amplitude characteristics between a non-dot interference region where dot interference does not occur and a dot interference region where dot interference occurs. FIG. 15 shows the relationship between frequency and amplitude in an image, with the normalized angular frequency on the horizontal axis and the power spectrum of the amplitude on the vertical axis.

  Referring to FIG. 15, it can be seen that the image signal in the dot disturbing region has a signal component having a larger amplitude than the image signal in the non-dot disturbing region between the bands of frequency a and frequency b. Therefore, similarly to the determination disturbance area exclusion unit 102 according to the first and second configuration examples described above, the determination disturbance area exclusion unit 102 according to the third configuration example is an image signal of the non-dot interference area illustrated in FIG. By using the difference between the image signal in the dot interference area and the image signal in the dot interference area, it is possible to exclude the image signal in the dot interference area that can be a determination interference factor. Here, the dot interference is a kind of noise that can be generated in the contour portion when the luminance signal and the color signal cannot be accurately separated. The image determination apparatus 100 can reduce the possibility of erroneous determination due to the influence of noise by excluding the area where dot interference has occurred. Therefore, the image determination apparatus 100 can determine an image more accurately.

[Determination Interference Area Exclusion Unit 102 According to Third Configuration Example]
FIG. 16 is a block diagram illustrating a third configuration example of the determination interference area excluding unit 102 according to the first embodiment of the present invention. Referring to FIG. 16, the determination interference area exclusion unit 102 according to the third configuration example includes a dot interference area detection unit 400 and a non-dot interference area detection unit 402.

  The dot interference area detection unit 400 detects a dot interference area based on the input image signal and outputs dot interference area information. Here, as means for detecting the dot interference area, for example, the techniques of Patent Nos. 3916041 and 3916042 for which the applicant of the present application has a patent right may be used, but are not limited thereto.

  The non-dot interference area detection unit 402 detects an area other than the dot interference area, that is, a non-dot interference area, based on the dot interference area information output from the dot interference area detection unit 400. Therefore, the image signal output from the non-dot interference area detection unit 402 is an image signal from which the image signal of the dot interference area that can be a determination interference factor is excluded.

  The determination interference area exclusion unit 102 according to the third configuration example can output, for example, an image signal in which an image signal of a dot interference area that can be a determination interference factor is excluded by the configuration illustrated in FIG.

  Note that the configuration of the determination interference area exclusion unit according to the third configuration example is not limited to the above. For example, the determination interference area exclusion unit according to the third configuration example includes only the non-dot interference area detection unit, and the image processing apparatus according to the first embodiment includes a dot interference area detection unit (not shown) separately provided. Based on the area information, it is also possible to output an image signal from which the image signal of the dot disturbance area that can be a determination disturbance factor is excluded by the determination disturbance area exclusion unit according to the third configuration example.

[Fourth Configuration Example of Judgment Interference Area Exclusion Unit 102: Exclusion of Mosaic Area]
As described above, the determination interference factors are not limited to high-definition CG, block distortion, and dot interference. Therefore, as a fourth configuration example of the determination interference area exclusion unit 102, a configuration corresponding to the determination interference factor shown in (4) above, that is, a configuration capable of excluding an image area on which a mosaic image is superimposed. Will be described. Here, since the image region on which the mosaic image is superimposed is a region in which another image (mosaic image) is superimposed on the base image, it can be regarded as a kind of noise in image determination. The image determination apparatus 100 can reduce the possibility of erroneous determination due to the influence of noise by excluding the region where the mosaic image is superimposed. Therefore, the image determination apparatus 100 can determine an image more accurately.

[Determination Interference Area Exclusion Unit 102 According to Fourth Configuration Example]
FIG. 17 is a block diagram illustrating a fourth configuration example of the determination interference area exclusion unit 102 according to the first embodiment of the present invention. Referring to FIG. 17, the determination disturbance region exclusion unit 102 according to the fourth configuration example includes a mosaic region detection unit 500 and a non-mosaic region detection unit 502.

  The mosaic area detection unit 500 detects a mosaic area based on the input image signal and outputs mosaic area information.

  The non-mosaic region detection unit 502 detects a region other than the mosaic region, that is, a non-mosaic region based on the mosaic region information output from the mosaic region detection unit 500. Therefore, the image signal output from the non-mosaic region detection unit 502 is an image signal from which the image signal of the mosaic region that can be a determination disturbing factor is excluded.

  The determination interference area exclusion unit 102 according to the fourth configuration example can output, for example, an image signal in which an image signal of a mosaic area that can be a determination interference factor is excluded by the configuration illustrated in FIG.

  Note that the configuration of the determination interference area exclusion unit according to the fourth configuration example is not limited to the above. For example, region information from a mosaic region detection unit (not shown) separately provided in the image processing apparatus according to the first embodiment, in which the determination interference region exclusion unit according to the fourth configuration example includes only the non-mosaic region detection unit. Based on the above, it is also possible to output an image signal from which an image signal of a mosaic area that can be a determination disturbance factor is excluded by the determination disturbance area exclusion unit according to the fourth configuration example.

[Fifth Configuration Example of Judgment Interference Area Exclusion Unit 102: Exclusion of Side Panel Area]
As described above, the determination interference factor is not limited to high-definition CG, block distortion, dot interference, and mosaic image superimposition. Therefore, as a fifth configuration example of the determination interference area exclusion unit 102, a configuration corresponding to the determination interference factor shown in (5) above, that is, a configuration capable of excluding an area to which a side panel is added. explain. Here, since the region to which the side panel is added is a region in which another image (side panel) is added to the base image, it can be regarded as a kind of noise in image determination. The image determination apparatus 100 can reduce the possibility of erroneous determination due to the influence of noise by excluding the region to which the side panel is added. Therefore, the image determination apparatus 100 can determine an image more accurately.

[Determination Interference Area Exclusion Unit 102 According to Fifth Configuration Example]
FIG. 18 is a block diagram illustrating a fifth configuration example of the determination interference area exclusion unit 102 according to the first embodiment of the present invention. Referring to FIG. 18, the determination interference region exclusion unit 102 according to the fifth configuration example includes a side panel region detection unit 600 and a non-side panel region detection unit 602.

  The side panel area detection unit 600 detects a side panel area based on the input image signal and outputs side panel area information. Here, as a means for detecting the side panel region, for example, the technique disclosed in Japanese Patent Application Laid-Open No. 2005-354187 may be used, but is not limited thereto.

  The non-side panel area detection unit 602 detects an area other than the side panel area, that is, a non-side panel area, based on the side panel area information output from the side panel area detection unit 600. Therefore, the image signal output from the non-side panel region detection unit 602 is an image signal from which the image signal of the side panel region that can be a determination interference factor is excluded.

  The determination disturbance area exclusion unit 102 according to the fifth configuration example can output, for example, an image signal from which an image signal of a side panel area that can be a determination disturbance factor is excluded by the configuration illustrated in FIG.

  Note that the configuration of the determination interference area exclusion unit according to the fifth configuration example is not limited to the above. For example, the determination interference region exclusion unit according to the fifth configuration example includes only the non-side panel region detection unit, and the non-side panel region detection unit may set a region in the center of the image (a side panel may be added). By detecting the non-side panel area as a non-side panel area, it is possible to output an image signal from which the image signal of the side panel area is excluded.

  Further, the determination disturbance area exclusion unit according to the fifth configuration example is based on area information from a side panel area detection unit (not shown) separately provided in the image processing apparatus according to the first embodiment. It is also possible to output an image signal from which the image signal of the potential side panel region is excluded. Furthermore, the determination disturbance region exclusion unit according to the fifth configuration example includes a reliability (for example, detection information) of region information from a side panel region detection unit (not shown) separately provided in the image processing apparatus according to the first embodiment. By determining the index based on accuracy, when the reliability is low, it is possible to detect a preset area in the center of the image as a non-side panel area.

[Sixth Configuration Example of Judgment Interference Area Exclusion Unit 102]
In the above, as the determination interference region exclusion unit according to the first to fifth configuration examples, high-definition CG superimposition, block distortion generation, dot interference generation, mosaic image superimposition, or side panel addition determination interference A configuration that is excluded as a factor is shown. However, the determination disturbance area exclusion unit 102 according to the first embodiment of the present invention is not limited to the first to fifth configurations. For example, the determination interference region exclusion unit 102 according to the first embodiment of the present invention can arbitrarily combine the first to fifth configurations. Since the judgment interference area exclusion unit 102 has a configuration in which the first to fifth configurations are arbitrarily combined, any judgment interference factor among high-definition CG, block distortion, dot interference, mosaic image, or side panel is excluded. can do.

  As described above with reference to FIGS. 5 to 18, the determination interference area exclusion unit 102 detects an area having a determination interference factor that may cause an erroneous determination, and an image signal of the area having the determination interference factor is detected. The excluded image signal can be output.

  With reference to FIG. 4 again, the image determination apparatus 100 according to the first embodiment of the present invention will be described.

  The frequency band signal detection unit 104 includes a first frequency band signal detection unit 150 and a second frequency band signal detection unit 152, and performs filtering of an input image signal. For example, the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152 perform processing for each pixel, pass only an image signal in a specific frequency band, and attenuate image signals in other bands. It can be composed of BPF.

  For example, the first frequency band signal detection unit 150 passes a frequency band lower than the upper limit of the theoretically effective frequency for the Nyquist frequency in an image upconverted from an SD resolution image, and does not pass a DC component. Consists of low-frequency BPF.

  Further, the second frequency band signal detection unit 152 includes, for example, a mid-band BPF that passes the vicinity of the upper limit of the theoretically effective frequency with respect to the Nyquist frequency in the image up-converted from the SD resolution image. Here, the low frequency band BPF constituting the first frequency band signal detection unit 150 and the middle frequency band BPF constituting the second frequency band signal detection unit 152 may partially overlap the frequency band.

  The method for up-converting an SD resolution image to an HD resolution image is not limited to the side panel method, and examples thereof include a top & bottom crop method and a stretch method. The upper limit of the theoretically effective frequency for the Nyquist frequency in an image up-converted from an SD resolution image varies depending on the up-conversion method. That is, as shown in FIG. 2, when the normalized Nyquist frequency in the HD resolution and the pseudo HD resolution is a (a = π), the image of the up-converted image by the top & bottom crop method and the stretch method is used. The upper limit b of the theoretically effective frequency for the Nyquist frequency is b = (3/8) × a, and the upper limit c of the theoretically effective frequency for the Nyquist frequency of the image up-converted by the side panel method is c = (4/9) × a.

  Therefore, the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152, for example, set the first frequency band signal detection unit 150 based on the theoretically effective upper limit b for the Nyquist frequency, The second frequency band signal detector 152 can be set based on the theoretically effective upper limit c for the Nyquist frequency. Note that the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152 are not limited to the above, and both the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152 are Nyquist. The upper limit b or the upper limit c of the theoretically effective frequency for the frequency may be set as a reference.

  In addition, the BPF constituting the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152 needs to reduce the side lobes in order to increase the detection capability. Therefore, the BPF according to the first embodiment sets a filter coefficient value using, for example, a function obtained by multiplying a Sinc function by a Hamming window function, and taps so as to correspond to the filter coefficient value. Configure the BPF by setting the number.

  By adopting the above configuration, the BPF according to the first embodiment can reduce the side lobes and can bring the main lobe closer to the rectangular wave, rather than using the discrete Fourier transform. Needless to say, the window function used to set the filter coefficient value is not limited to the Hamming window function, and a Hanning window function or a Gaussian window function can be used. In addition, the BPF according to the first embodiment is not limited to the above configuration, and may be configured with a digital filter.

  In addition, the 1st frequency band signal detection part 150 and the 2nd frequency band signal detection part 152 can also be comprised by HPF. Also, the first frequency band signal detection unit 150 and the second frequency band signal detection unit 152 can be configured by a low-pass filter. However, when a low-pass filter is used, it is affected by the average luminance corresponding to a signal having a frequency of 0 (zero), and the HD luminance image and the pseudo HD resolution image cannot be accurately determined by the average luminance. There is.

  Therefore, the frequency band signal detection unit 104 is preferably a filter that does not allow an image signal having a frequency of 0 (zero) to pass therethrough, and is not limited to a BPF, and can be configured by an arbitrary filter.

  The noise removal unit 106 includes a first noise removal unit 154 and a second noise removal unit 156, and can remove noise from the image signal output from the frequency band signal detection unit 104. The first noise removing unit 154 removes noise of the image signal filtered for each pixel by the first frequency band signal detecting unit 150 and outputs an amplitude characteristic value for each pixel. The second noise removing unit 156 removes noise of the image signal filtered by the second frequency band signal detecting unit 152 for each pixel.

  Here, the noise removal in the noise removal unit 106 can be performed, for example, by setting in advance a threshold value of an amplitude characteristic value regarded as noise for each frequency band that the frequency band signal detection unit 104 passes.

  The average value calculation unit 108 includes a first average value calculation unit 158 and a second average value calculation unit 160, and can calculate the average value of the amplitude characteristic values output from the noise removal unit 106. The amplitude characteristic value for each pixel from which noise has been removed by the first noise removing unit 154 is input to the first average value calculating unit 158, and the first average value calculating unit 158 is an average value of absolute values of the amplitude characteristic values. Is calculated. Further, the amplitude characteristic value for each pixel from which noise has been removed by the second noise removal unit 156 is input to the second average value calculation unit 160, and the second average value calculation unit 160 calculates the absolute value of the amplitude characteristic value. The average value is calculated.

  Here, the average value in the 1st average value calculation part 158 and the 2nd average value calculation part 160 can be calculated | required by an arithmetic mean, for example. It should be noted that the average value calculation method in the average value calculation unit 108 is not limited to the arithmetic average, and can be calculated by various methods such as a geometric average and a weighted average.

  The relative value calculation unit 110 uses the output of the average value calculation unit 108, that is, the average value of the absolute values of the amplitude characteristic values output from the first average value calculation unit 158 and the second average value calculation unit 160, respectively. To calculate the relative value. Here, the relative value calculated by the relative value calculation unit 110 corresponds to the HD degree shown in Equation 1. Therefore, the calculation of the relative value in the relative value calculation unit 110 can be obtained according to Equation 1 according to Equation 2 shown below, for example.

HD degree = relative value calculated by the relative value calculation unit 110 = (average value calculated by the second average calculation unit 160) / (average value calculated by the first average calculation unit 158)
... (Formula 2)

  Note that the relative value calculated by the relative value calculation unit 110, that is, the method of calculating the HD degree is not limited to Formula 2, and for example, it can be obtained by Formula 3 below using a logarithm (common logarithm).

HD degree = relative value calculated by the relative value calculation unit 110 = log (average value calculated by the second average calculation unit 160) −log (average value calculated by the first average calculation unit 158)
... (Formula 3)

  The sample number reliability setting unit 112 sets the first reliability based on the number (sample number) of pixels whose amplitude characteristic value is non-zero (zero). Here, the reason why the image determination apparatus 100 sets the first reliability is as follows.

[Reason for setting first reliability]
For example, the image determination apparatus 100 determines an image using the HD degree shown in Equation 1. However, the smaller the number of samples for calculating the average value shown in Equation 1, the lower the statistical reliability of the average value. Therefore, when the HD degree is calculated using an average value having a low statistical reliability, the image determination apparatus 100 determines whether the image indicated by the input image signal is an HD resolution image or a pseudo HD resolution image. It is not always possible to accurately determine whether the image is an image.

  Therefore, the image determination apparatus 100 attempts to reduce the possibility of erroneous determination by setting the reliability with respect to the number of samples for calculating the average value. Hereinafter, the sample number reliability setting unit 112 will be described in more detail.

  The sample number reliability setting unit 112 outputs the first sample number reliability setting unit 162 that sets the first reliability based on the image signal output from the first noise removal unit 154 and the second noise removal unit 156. A second sample number reliability setting unit 164 that sets the first reliability based on the image signal to be processed.

  Here, the setting of the first reliability in each of the first sample number reliability setting unit 162 and the second sample number reliability setting unit 164 can be performed by, for example, the following procedures (I) and (II). . In the following, the setting of the first reliability in the first sample number reliability setting unit 162 will be described as an example, but the second sample number reliability setting unit 164 can similarly set the first reliability.

[Example of first reliability setting procedure]
(I) Calculation of the number of samples The first sample number reliability setting unit 162 determines whether or not the amplitude characteristic value is non-zero (zero) for each pixel and calculates the number of samples. Here, as a method for calculating the number of samples, for example, every time the amplitude characteristic value is determined to be non-zero (zero), the value of the counter is increased by 1. However, the method is not limited to the above.

(II) First reliability setting The first sample number reliability setting unit 162 sets the first reliability based on the calculated number of samples. Here, the first sample number reliability setting unit 162 can set the first reliability by, for example, comparing the calculated sample number with a predetermined threshold. For example, the first sample number reliability setting unit 162 sets the first reliability to “1” when the calculated sample number is equal to or greater than a predetermined threshold (that is, the sample number is calculated by the average value calculation shown in Equation 1). The first reliability is “0” when the calculated number of samples is less than a predetermined threshold (that is, the number of samples is the average shown in Equation 1). It is a value that cannot be used for value calculation.). The predetermined threshold used for setting the first reliability can be, for example, a fixed value defined in advance, but is not limited to the above, and may be a value that varies according to user input. Needless to say, the first reliability setting method is not limited to the above. Further, the first reliability set by the first sample number reliability setting unit 162 is not limited to the above-described binary value (“0” or “1”).

  The predetermined threshold value used by the first sample number reliability setting unit 162 for setting the first reliability is, for example, the sample number reliability setting unit 112 including a storage unit (or the first sample number reliability). The setting unit 162 may include a storage unit), and may be stored in the storage unit. Here, examples of the storage unit included in the sample number reliability setting unit 112 include non-volatile memories such as an EEPROM and a flash memory, but are not limited thereto. The predetermined threshold value used for setting the first reliability is stored in, for example, a storage unit (not shown) of the image determination apparatus 100, and the first sample number reliability setting unit 162 stores the storage unit (see FIG. Needless to say, it may be read appropriately from (not shown).

  The sample number reliability setting unit 112 can set the first reliability for each local region, for example, by the procedures (I) and (II).

  The average value reliability setting unit 114 sets a second reliability based on the average value calculated by the average value calculation unit 108. Here, the reason why the image determination apparatus 100 sets the second reliability is as follows.

[Reason for setting second reliability]
As described above, the image determination apparatus 100 determines an image using, for example, the HD degree shown in Formula 1. However, when the average value shown in Formula 1 is a very small value, for example, the influence of noise (for example, noise that cannot be removed by the noise removing unit 106) becomes large, and thus the reliability of the average value. Can decline. Therefore, when the HD degree is calculated using an average value with low reliability, the image determination apparatus 100 determines whether the image indicated by the input image signal is an HD resolution image or a pseudo HD resolution image. It cannot always be determined accurately.

  Therefore, the image determination apparatus 100 attempts to reduce the possibility of erroneous determination by setting the reliability for the calculated average value. Hereinafter, the average value reliability setting unit 114 will be described more specifically.

  The average value reliability setting unit 114 includes a first average value reliability setting unit 166 that sets the second reliability based on the average value output from the first average value calculation unit 158, and a second average value calculation unit 160. And a second average value reliability setting unit 168 that sets the second reliability based on the average value output from.

  Here, the setting of the second reliability in each of the first average value reliability setting unit 166 and the second average value reliability setting unit 168 can be performed as follows, for example. Hereinafter, the setting of the second reliability in the first average value reliability setting unit 166 will be described as an example, but the second average value reliability setting unit 168 can similarly set the second reliability.

[Example of second reliability setting procedure]
The first average value reliability setting unit 166 can set the second reliability by comparing the average value output from the first average value calculation unit 158 with a predetermined threshold value. For example, the first average value reliability setting unit 166 sets the second reliability to “1” when the average value output from the first average value calculation unit 158 is equal to or greater than a predetermined threshold (that is, the average value is This is a value that can be used for calculating the HD degree shown in Equation 1.), and the second reliability is set when the average value output from the first average value calculating unit 158 is less than a predetermined threshold. It can be set to “0” (that is, the average value is a value that cannot be used for calculating the HD degree shown in Equation 1). The predetermined threshold used for setting the second reliability can be, for example, a predetermined fixed value, but is not limited to the above, and may be a value that varies according to user input. Needless to say, the method of setting the second reliability is not limited to the above. Further, the second reliability set by the first average value reliability setting unit 166 is not limited to the above-described binary value (“0” or “1”).

  The predetermined threshold used by the first average value reliability setting unit 166 for setting the second reliability is, for example, the average value reliability setting unit 114 including a storage unit (or the first average value reliability). The setting unit 166 may include a storage unit), and may be stored in the storage unit. Here, examples of the storage unit included in the average value reliability setting unit 114 include non-volatile memories such as an EEPROM and a flash memory, but are not limited thereto. Note that the predetermined threshold value used for setting the second reliability is stored in, for example, a storage unit (not shown) of the image determination apparatus 100, and the first average value reliability setting unit 166 stores the storage unit (see FIG. Needless to say, it may be read appropriately from (not shown).

  The average value reliability setting unit 114 can set the second reliability for each local region, for example, by the procedure as described above.

  Based on the first reliability output from the sample number reliability setting unit 112 and the second reliability output from the average value reliability setting unit 114, the reliability setting unit 116 allows the relative value calculation unit 110 to A relative value to be calculated, that is, a third reliability that is a reliability with respect to the HD degree in Expression 1 is set.

[Example of third reliability setting procedure]
The reliability setting unit 116 includes a first reliability (first first reliability) set by the first sample number reliability setting unit 162 and a first reliability (first reliability set by the second sample number reliability setting unit 164 ( Second first reliability), second reliability set by the first average value reliability setting unit 166 (first second reliability), and second set by the second average value reliability setting unit 168. The third reliability can be set based on the reliability (second second reliability).

  The reliability setting unit 116 can set the third reliability by, for example, an AND operation. That is, the reliability setting unit 116, for example, when the first first reliability, the second first reliability, the first second reliability, and the second second reliability are all “1”. The third reliability can be set to “1” (that is, the relative value calculated by the relative value calculation unit 110 can be used for image determination). In addition, the reliability setting unit 116 is, for example, one of the first first reliability, the second first reliability, the first second reliability, and the second second reliability is “0”. In this case, the third reliability can be set to “0” (that is, the relative value calculated by the relative value calculation unit 110 is not usable for image determination). Needless to say, the setting criterion of the third reliability is not limited to the above.

  For example, the reliability setting unit 116 can set the third reliability by the procedure as described above.

  Based on the relative value calculated by the relative value calculation unit 110 and the third reliability set by the reliability setting unit 116, the image determination unit 118, for example, as shown in (A) and (B) below. Image determination can be performed.

[Determination of Image in Image Determination Unit 118]
(A) When the third reliability is “1” (when the third reliability is high)
When the third reliability is “1”, the image determination unit 118 can perform image determination using the relative value calculated by the relative value calculation unit 110. Further, the image determination unit 118 can record a relative value used for image determination. Here, the image determination unit 118 can record the relative value in, for example, a storage unit included in the image determination unit 118, but is not limited thereto, and is recorded in a storage unit (not shown) included in the image determination apparatus 100. May be. Examples of the storage means included in the image determination unit 118 include non-volatile memories such as an EEPROM and a flash memory. However, the storage unit is not limited to the above. For example, an SDRAM (Synchronous Dynamic Random Access Memory) or an SRAM (Static Random Access Memory). It may be a volatile memory.

(B) When the third reliability is “0” (when the third reliability is low)
When the third reliability is “0”, the image determination unit 118 can perform image determination using the relative value that was used when the previous image determination was normally performed. Here, for example, the image determination unit 118 may read a relative value from a storage unit included in the image determination unit 118, or may read out a relative value from a storage unit (not shown) included in the image determination apparatus 100. When the image determination unit 118 cannot read the relative value, the image determination unit 118 can output a predetermined image determination result, for example. However, the image determination unit 118 is not limited to the above. The determination may not be performed.

  For example, the image determination unit 118 can determine an image as shown in (A) and (B) above.

  As described above, the image determination device 100 according to the first embodiment of the present invention detects an area having a determination disturbance factor that can cause an erroneous determination from an input image signal, and detects an area having a determination disturbance factor. An image signal from which the image signal is excluded can be output. Then, the image determination apparatus 100 has a frequency amplitude characteristic of an HD resolution image and a pseudo HD resolution image as illustrated in FIG. 2 with respect to an image signal from which an image signal of a region having a determination interference factor is excluded. By using the difference, the image can be determined based on the relative value of the average value of the amplitude characteristic value in the middle frequency band with respect to the average value of the amplitude characteristic value in the low frequency band.

  Therefore, the image determination apparatus 100 according to the first embodiment of the present invention does not require a side panel to be added when an SD resolution image is up-converted, unlike the conventional image determination apparatus. Therefore, the determination of the image can be performed more strictly regardless of the up-conversion method of the image.

  Further, the image determination apparatus 100 can perform image determination on the image signal from which the image signal in the region having the determination interference factor is excluded, thereby reducing the possibility of erroneous determination (preventing erroneous determination). In addition, more accurate image determination can be performed.

(Program for image determination)
The above-described program for causing the image determination apparatus 100 according to the first embodiment of the present invention to function as a computer does not depend on the up-conversion method of the image, and the reliability of the image determination result. It is possible to determine an image after removing a factor that reduces the image quality.

(Image determination method according to the first embodiment)
Next, an image determination method according to the first embodiment of the present invention will be described. FIG. 19 is a flowchart showing an example of an image determination method according to the first embodiment of the present invention.

  First, the image determination apparatus detects a determination disturbance area that is an area having a determination disturbance factor (S200). Here, examples of the determination disturbance factor to be detected in step S200 include high-definition CG superimposition, block distortion, dot disturbance, mosaic image superimposition, or side panel addition. Moreover, the image determination apparatus can detect a determination interference area | region by providing the determination interference area exclusion part which concerns on the 1st-6th structural example mentioned above, for example.

  The image determination apparatus excludes the determination interference area detected in step S200, and outputs an image signal from which the image signal of the determination interference area is excluded (S202).

  Based on the image signal from which the image signal of the determination interference area output in step S202 is excluded, the image determination apparatus determines an image (S204). Here, the image determination in step S204 can be performed using, for example, the difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image as shown in FIG.

  As shown in steps S200 to S204 above, the image determination method according to the first embodiment of the present invention prevents erroneous determination of an image due to a determination interference factor by detecting and excluding the determination interference region. can do.

  In addition, the image determination method according to the first embodiment can determine an image using a difference in frequency amplitude characteristics between an HD resolution image and a pseudo HD resolution image as shown in FIG. Therefore, the image determination apparatus using the image determination method according to the first embodiment can perform image determination regardless of the up-conversion method of the image.

(Second Embodiment)
In the above, as the first embodiment of the image determination apparatus according to the embodiment of the present invention, the image determination apparatus that determines an image by the process described in the outline of the first determination process described above has been described. However, the image determination apparatus according to the embodiment of the present invention is not limited to the configuration in which the image is determined by the process shown in the outline of the first determination process described above. Therefore, next, an image determination apparatus according to a second embodiment capable of performing image determination by the process shown in the outline of the second determination process described above will be described.

  FIG. 20 is a block diagram showing an image determination apparatus 700 according to the second embodiment of the present invention. Here, the image determination apparatus 700 can determine an image by the process shown in the outline of the second determination process described above.

  Referring to FIG. 20, an image determination apparatus 700 according to the second embodiment of the present invention has basically the same configuration as that of the image determination apparatus 100 according to the first embodiment. Compared with the determination apparatus 100, a determination interference region detection unit 702 is provided instead of the determination interference region exclusion unit 102, and the frequency band signal detection unit 704 is different.

  In addition, the image determination apparatus 700 is similar to the image determination apparatus 100 according to the first embodiment, for example, a control unit (not shown) configured by an MPU or the like, a ROM (not shown), a RAM (see FIG. (Not shown), a memory | storage part (not shown), a receiving part (not shown), an operation part (not shown), etc. may be provided.

  The determination interference area detection unit 702 detects a determination interference area, which is an area having a determination interference factor, based on the input image signal. Here, examples of the determination interference factor detected by the determination interference area detection unit 702 include high-definition CG superimposition, block distortion, dot interference, mosaic image superimposition, and side panel addition. .

  Here, the determination interference area detection unit 702 includes, for example, the above-described high-definition CG area detection unit 200 (FIG. 6), block distortion area detection unit 300 (FIG. 14), dot interference area detection unit 400 (FIG. 16), mosaic. The configuration may be the same as or combined with each of the region detection unit 500 (FIG. 17) and the side panel region detection unit 600 (FIG. 18).

  Further, the determination interference area detection unit 702 can output detection result information corresponding to the detected result. Here, the detection result information output by the determination disturbance area detection unit 702 can be expressed by digital data of predetermined bits (bits) indicating the type and position of the detected determination disturbance factor, for example. Not limited.

  The frequency band signal detection unit 704 includes a first frequency band signal detection unit 710 and a second frequency band signal detection unit 712, and is input in the same manner as the frequency band signal detection unit 104 according to the first embodiment. Filter the image signal. Here, the difference between the frequency band signal detection unit 704 and the frequency band signal detection unit 104 according to the first embodiment is that the frequency band signal detection unit 704 outputs detection result information from the determination interference region detection unit 702. The cut-off frequency is changed according to the above.

  In general, in the case of a natural image (non-CG image), the spectrum tends to be small around the Nyquist frequency band for the resolution of the image. On the other hand, for example, in the case of a CG image, in the vicinity of the Nyquist frequency band corresponding to the resolution of the CG image, the spectrum tends to be larger than the spectrum of a natural image of the same resolution. Therefore, when a high-definition HD resolution image and an image up-converted from an SD resolution image are discriminated by frequency band detection processing, for example, the determination is made by changing the frequency band to be detected between a natural image and a CG image. It becomes possible to exclude the influence of the disturbing factor (that is, the accuracy of image determination can be improved).

  The first frequency band signal detection unit 710 is, for example, a frequency band lower than the Nyquist frequency in an image up-converted from an SD resolution image, similarly to the first frequency band signal detection unit 150 according to the first embodiment. And a low-frequency BPF that does not allow the DC component to pass.

  The second frequency band signal detection unit 712 can be configured with a BPF in the same manner as the second frequency band signal detection unit 152 according to the first embodiment. For example, the detection output from the determination interference region detection unit 702 When the result information indicates a natural image (non-CG image), a band slightly lower than the theoretically effective frequency corresponding to the up-conversion method of the SD resolution image is set as the lower cutoff frequency.

  In addition, the second frequency band signal detection unit 712 theoretically corresponds to the up-conversion method of the SD resolution image when the detection result information output from the determination interference region detection unit 702 indicates a CG image, for example. Set the effective frequency band as the lower cutoff frequency.

  In the above, a CG image is illustrated, but the frequency band signal detection unit 704 also sets the cutoff frequency according to the detection result information output from the determination interference region detection unit 702 for other determination interference factors. Can be changed. Further, the first frequency band signal detection unit 710 and the second frequency band signal detection unit 712 are not limited to the BPF, and may be configured by an HPF, for example. Furthermore, in the image determination apparatus 700 illustrated in FIG. 20, the configuration in which the detection result information output from the determination interference region detection unit 702 is input to the second frequency band signal detection unit 712 has been described. Such an image determination apparatus is not limited to such a configuration, and for example, detection result information can also be input to the first frequency band signal detection unit 710.

  In addition, the noise removal unit 106, the average value calculation unit 108, the relative value calculation unit 110, the sample number reliability setting unit 112, the average value reliability setting unit 114, the reliability setting unit 116, and the image determination included in the image determination device 700 The unit 118 can have the same function as that of the image determination apparatus 100 according to the first embodiment. Therefore, the image determination apparatus 700 uses the difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image as shown in FIG. 2 and uses the difference between the average amplitude characteristic values in the low frequency band. The image can be determined based on the relative value of the average value of the amplitude characteristic values in the frequency band.

  As described above, the image determination apparatus 700 according to the second embodiment detects an area having a determination disturbing factor that may cause an erroneous determination from the input image signal, and the image signal input according to the detection result. By appropriately changing the cut-off frequency for filtering the determination disturbance factor, it is possible to exclude the determination interference factor. Then, the image determination apparatus 700 uses the difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image as shown in FIG. The image can be determined based on the relative value of the average value of the amplitude characteristic value in the middle frequency band to the average value of the amplitude characteristic value in the frequency band of the band.

  Therefore, the image determination apparatus 700 according to the second embodiment of the present invention does not require a side panel to be added when an SD resolution image is up-converted, unlike the conventional image determination apparatus. Therefore, the determination of the image can be performed more strictly regardless of the up-conversion method of the image.

  Further, the image determination apparatus 700 can perform image determination on the image signal from which the determination interference factor is excluded, so that the possibility of erroneous determination is reduced (preventing erroneous determination), and a more accurate image is obtained. Can be determined.

  As described above, the image determination apparatus has been described as the first and second embodiments of the present invention. However, the first and second embodiments of the present invention are not limited to such a form, and are a television receiver and an organic EL. It is also called a display (organic ElectroLuminescence display). ), FED (Field Emission Display) or PDP (Plasma Display Panel), display devices such as PDA (Personal Digital Assistants) and UMPC (Ultra Mobile Personal Computer), mobile phones and PHS (PHS) It can be applied to portable communication devices such as Personal Handyphone System).

(Program for image determination)
The above-described program for causing the image determination apparatus 700 according to the second embodiment of the present invention to function as a computer does not depend on the up-conversion method of the image, and the reliability of the image determination result. It is possible to determine an image after removing a factor that reduces the image quality.

(Image determination method according to the second embodiment)
Next, an image determination method according to the second embodiment of the present invention will be described. FIG. 21 is a flowchart showing an example of an image determination method according to the second embodiment of the present invention.

  First, as in the first determination method, the image determination apparatus detects a determination interference area that is an area having a determination interference factor (S300).

  In accordance with the detection result in step S300, the image determination device changes the cutoff frequency for filtering the input image signal (S302).

  The image determination device filters the image signal input at the cutoff frequency changed in step S302, and determines the image as in the first determination method (S304).

  As shown in steps S300 to S304 above, the image determination method according to the second embodiment of the present invention detects a determination interference region and changes the cutoff frequency according to the detection result, thereby determining the determination interference factor. It is possible to prevent erroneous determination of an image due to the above.

  In addition, the image determination method according to the second embodiment can determine an image using a difference in frequency amplitude characteristics between an HD resolution image and a pseudo HD resolution image as shown in FIG. Therefore, the image determination apparatus using the image determination method according to the second embodiment can perform image determination regardless of the up-conversion method of the image.

  As mentioned above, although preferred embodiment of this invention was described referring an accompanying drawing, it cannot be overemphasized that this invention is not limited to the example which concerns. It will be apparent to those skilled in the art that various changes and modifications can be made within the scope of the claims, and these are naturally within the technical scope of the present invention. Understood.

  For example, in the image determination apparatus according to the first and second embodiments of the present invention described above, the configuration in which the average value calculation unit that calculates the average value is provided is shown. It can also be a value calculation unit. Even if the relative value is calculated using the median value instead of the average value, it is possible to use the difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image as shown in FIG. Therefore, the image determination apparatus can determine an image.

  Moreover, in the image determination apparatus according to the first and second embodiments of the present invention, the configuration including the noise removing unit has been described. However, the configuration is not limited thereto, and a configuration not including the noise removing unit may be employed. . As described above, the image determination apparatus according to the embodiment of the present invention determines an image using a difference in frequency amplitude characteristics between an HD resolution image and a pseudo HD resolution image as shown in FIG. Therefore, even if the image is affected by the noise, the image can be determined regardless of the up-conversion method of the image.

  The image determination apparatus according to the first and second embodiments has a configuration in which the frequency band signal detection unit filters the image signal by the first frequency band signal detection unit and the second frequency band signal detection unit. The embodiment of the present invention is not limited to such a configuration. For example, in the image determination apparatus according to the embodiment of the present invention, the frequency band signal detection unit has a first frequency band signal detection unit to an nth frequency band signal detection unit (where n is an integer of 3 or more). It is also possible to calculate a plurality of HD degrees (relative values) shown in Formula 1 based on the image signals filtered by the plurality of frequency band signal detection units. Even with such a configuration, since the difference in frequency amplitude characteristics between the HD resolution image and the pseudo HD resolution image as shown in FIG. 2 can be used, the image determination apparatus performs image determination. Can do. As an image determination method using a plurality of calculated HD degrees (relative values), for example, the total number of relative values whose HD degrees (relative values) are less than a predetermined threshold and HD degrees (relative values) are predetermined. Although it can be performed by comparing the total number of HD degrees (relative values) equal to or greater than the threshold, which is larger, it is not limited to the above.

  Furthermore, the image determination device according to the first and second embodiments includes a sample number reliability setting unit, an average value reliability setting unit, and a reliability setting unit, and the reliability for the HD degree shown in Equation 1 is an image. Although the configuration used for the determination is shown, the embodiment of the present invention is not limited to this configuration. For example, the image determination apparatus according to the embodiment of the present invention may not include the sample number reliability setting unit, the average value reliability setting unit, and the reliability setting unit. Even with such a configuration, the image determination apparatus according to the embodiment of the present invention determines an image using a difference in frequency amplitude characteristics between an HD resolution image and a pseudo HD resolution image as shown in FIG. Therefore, the image can be determined regardless of the up-conversion method of the image.

  It should be understood that the above-described configuration can be easily changed by those skilled in the art and belongs to the equivalent scope of the present invention.

It is explanatory drawing which shows the image of HD resolution, and the image which upconverted the image of SD resolution. FIG. 2 is an explanatory diagram for explaining a difference in frequency amplitude characteristics between an HD resolution image shown in FIG. 1A and a pseudo HD resolution image shown in FIG. It is explanatory drawing for demonstrating an example of the factor which may cause the misjudgment in the image determination apparatus which concerns on embodiment of this invention. It is a block diagram which shows the image determination apparatus which concerns on the 1st Embodiment of this invention. FIG. 4 is an explanatory diagram for explaining a difference in frequency amplitude characteristics between the image signal in the non-CG region shown in FIG. 3 and the image signal in the high-definition CG region shown in FIG. 3. It is a block diagram which shows the 1st structural example of the determination disturbance area | region exclusion part which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the 1st structural example of the disturbance area | region detection part which concerns on the 1st Embodiment of this invention. It is explanatory drawing for demonstrating the 1st detection means in the disturbance area | region detection part which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the 2nd structural example of the disturbance area | region detection part which concerns on the 1st Embodiment of this invention. It is explanatory drawing for demonstrating the 2nd detection means in the disturbance area | region detection part which concerns on the 1st Embodiment of this invention. It is a flowchart which shows an example of the detection method of the high-definition CG area | region in the 2nd CG area | region detection part which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the 3rd structural example of the disturbance area | region detection part which concerns on the 1st Embodiment of this invention. It is explanatory drawing explaining the difference of the frequency amplitude characteristic of the non-block distortion area | region where the block distortion has generate | occur | produced, and the block distortion area | region where the block distortion has generate | occur | produced. It is a block diagram which shows the 2nd structural example of the determination disturbance area | region exclusion part which concerns on the 1st Embodiment of this invention. It is explanatory drawing explaining the difference of the frequency amplitude characteristic of the non-dot interference area | region where dot interference has not generate | occur | produced, and the dot interference area | region where dot interference has generate | occur | produced. It is a block diagram which shows the 3rd structural example of the determination disturbance area exclusion part which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the 4th structural example of the determination disturbance area | region exclusion part which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the 5th structural example of the determination disturbance area exclusion part which concerns on the 1st Embodiment of this invention. It is a flowchart which shows an example of the image determination method which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the image determination apparatus which concerns on the 2nd Embodiment of this invention. It is a flowchart which shows an example of the image determination method which concerns on the 2nd Embodiment of this invention.

Explanation of symbols

100, 700 Image determination device 102 Judgment interference region exclusion unit 104, 204, 304, 704 Frequency band signal detection unit 106 Noise removal unit 108, 312 Average value calculation unit 110 Relative value calculation unit 112 Sample number reliability setting unit 114 Average value Reliability setting unit 116 Reliability setting unit 118 Image determination unit 202 Non-high definition CG region detection unit 206, 306 Characteristic value calculation unit 208 Flat region detection unit 210 Edge region detection unit 212, 314 Interference region detection unit 300 Block distortion region detection Unit 302 non-block distortion region detection unit 308 block boundary detection unit 310 variation value calculation unit 702 determination disturbance region detection unit

Claims (13)

A determination interference area exclusion unit that detects a determination interference area that hinders image determination based on an input image signal that is input and outputs an image signal corresponding to an area other than the determination interference area;
A first frequency band signal detection unit that detects signals in a plurality of frequency bands from the image signal output from the determination interference region exclusion unit;
A first average value calculating unit that calculates an average value of characteristic values corresponding to amplitudes for each of signals in a plurality of frequency bands detected by the first frequency band signal detecting unit;
A first relative value calculation unit that calculates a relative value of another average value with respect to one average value among the average values calculated for each of the plurality of frequency bands;
A first image determination unit that determines an image based on the calculated relative value;
An image determination apparatus comprising: The determination disturbance area exclusion unit is
A high-definition computer graphics area detecting unit for detecting a high-definition computer graphics area based on the input image signal;
A non-high-definition computer graphics region detection unit that detects a region other than the high-definition computer graphics region in accordance with a detection result in the high-definition computer graphics region detection unit, and outputs the image signal;
The image determination apparatus according to claim 1, further comprising: The high-definition computer graphics area detector
A second frequency band signal detector for detecting signals in a plurality of frequency bands from the input image signal;
A first characteristic value calculation unit that calculates a characteristic value corresponding to an amplitude for each of signals in a plurality of frequency bands detected by the second frequency band signal detection unit;
A flat region detecting unit that detects a flat region having the same characteristic value in the pixel unit based on the characteristic value calculated by the first characteristic value calculating unit;
An edge region detection unit that detects an edge region in units of pixels based on the characteristic value calculated by the first characteristic value calculation unit;
A first disturbing area detector for detecting the high-definition computer graphics area based on the detected flat area and the edge area;
The image determination apparatus according to claim 2, further comprising: The first disturbing area detector is
A first computer graphics area detecting unit that detects a nested area in which pixels in the flat area exist between pixels in the edge area as the high-definition computer graphics area;
An overdetection area exclusion unit that excludes an overdetection area from the detected high-definition computer graphics area;
The image determination apparatus according to claim 3, further comprising: The first disturbing area detector is
A pixel number detection unit for detecting the number of pixels in a nested region in which the pixels in the flat region exist between the pixels in the edge region;
A second computer graphic that divides an image indicated by the input image signal into a plurality of local regions and detects a high-definition computer graphics region for each local region based on the number of pixels detected by the pixel number detection unit A region detection unit;
The image determination apparatus according to claim 3, further comprising: The determination disturbance area exclusion unit is
A block distortion area detection unit for detecting a block distortion area based on the input image signal;
A non-block distortion region detection unit that detects a region other than the block distortion region according to a detection result in the block distortion region detection unit and outputs the image signal;
The image determination apparatus according to claim 1, further comprising: The block distortion region detection unit
A third frequency band signal detector for detecting signals in a plurality of frequency bands from the input image signal;
A second characteristic value calculation unit that calculates a characteristic value corresponding to the amplitude for each of the signals in the plurality of frequency bands detected by the third frequency band signal detection unit;
A block boundary detection unit for detecting a block boundary based on the input image signal;
A variation value calculation unit that calculates a variation value of the characteristic value for each block based on the detected block boundary and the one characteristic value calculated by the second characteristic value calculation unit;
A third average value calculating unit that calculates an average value of the characteristic values calculated by the second characteristic value calculating unit for each of the plurality of frequency bands;
A second disturbing region detection unit for detecting the block distortion region based on the calculated variation value or the average value;
The image determination apparatus according to claim 6, further comprising: A noise removing unit that removes the signal having the characteristic value less than a predetermined threshold for each of the signals of the plurality of frequency bands detected by the first frequency band signal detecting unit;
The image determination apparatus according to claim 1, wherein the first average value calculation unit calculates an average value of the characteristic values from which noise has been removed by the noise removal unit.   The first relative value calculator is configured to calculate the average value calculated in a predetermined frequency band determined in advance and the average value calculated in a frequency band higher than the predetermined frequency band determined in advance. The image determination apparatus according to claim 1, wherein the relative value is calculated based on the image.   The lower limit frequency of the predetermined frequency band is lower than the upper limit of the theoretically effective frequency according to the up-conversion method for the Nyquist frequency of the image up-converted from the standard resolution image, 10. The image according to claim 9, wherein a lower limit frequency of the frequency band is higher than a theoretically effective upper limit according to an up-conversion scheme for an Nyquist frequency of an image up-converted from a standard resolution image. Judgment device. A determination disturbance area detection unit that detects a determination disturbance area that hinders image determination based on an input image signal that is input;
A fourth frequency band signal detector for detecting signals in a plurality of frequency bands from the input image signal;
A fourth average value calculating unit that calculates an average value of characteristic values corresponding to amplitude for each of signals in a plurality of frequency bands detected by the fourth frequency band signal detecting unit;
A second relative value calculation unit that calculates a relative value of another average value with respect to one average value among the average values calculated for each of the plurality of frequency bands;
A second image determination unit that determines an image based on the calculated relative value;
With
The image determination apparatus according to claim 4, wherein the fourth frequency band signal detection unit changes the frequency band according to a detection result of the determination interference area in the determination interference area detection unit. Detecting a determination disturbing area that hinders image determination based on an input image signal to be input, and outputting an image signal corresponding to an area other than the determination disturbing area;
Detecting a plurality of frequency band signals from the image signal;
Calculating an average value of characteristic values corresponding to amplitude for each of the detected signals in the plurality of frequency bands;
Calculating a relative value of another average value with respect to one of the average values calculated for each of the plurality of frequency bands;
Determining an image based on the calculated relative value;
An image determination method characterized by comprising: Detecting a determination disturbing region that hinders image determination based on an input image signal to be input, and outputting an image signal corresponding to a region other than the determination disturbing region;
Detecting a plurality of frequency band signals from the image signal;
Calculating an average value of characteristic values corresponding to amplitude for each of the detected signals of the plurality of frequency bands;
Calculating a relative value of another average value with respect to one of the average values calculated for each of the plurality of frequency bands;
Determining an image based on the calculated relative value;
A program that causes a computer to execute.

Images