Decoding device and program

Abstract

To reduce block distortion for a high-luminance part of an SDR signal and also for an HDR signal without deteriorating a compression effect.SOLUTION: An encoding device 1 includes: a transformation unit 13 configured to calculate an orthogonal transform coefficient by performing an orthogonal transformation process on a residual image indicating a difference between an input image and a predicted image of the input image; a quantization unit 14 configured to generate a quantization coefficient by quantizing the orthogonal transform coefficient on the basis of a quantization parameter; an entropy encoding unit 24 configured to generate encoded data by encoding the quantization coefficient; an image decoding unit 10 configured to restore an orthogonal transform coefficient from the quantization coefficient on the basis of the quantization parameter and generate a reconstructed image by adding the predicted image to a residual image restored by performing inverse orthogonal transformation on the orthogonal transform coefficient; and a deblocking filtering unit 18 configured to perform a filtering process on the reconstructed image. The deblocking filtering unit 18 controls a filtering strength depending on a luminance signal level of the reconstructed image and the quantization parameter.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an encoding device, a decoding device, and a program that perform deblocking filter processing. [Background technology]

[0002] In mainstream video encoding schemes such as MPEG, the ease of real-time processing necessitates dividing video units, called frames (or pictures), into small block-like regions, and encoding (compression) is performed on a block-by-block basis using techniques such as transformation and prediction. In such encoding schemes, differences in encoding control between adjacent blocks result in perceived quality differences and distortions at block boundaries. Recent encoding schemes such as H.264 / AVC and H.265 / HEVC employ a process called deblocking filtering to reduce such encoding distortions.

[0003] Block distortion occurs as a result of signal degradation caused by the quantization of orthogonal transformation coefficients at the boundary between two adjacent blocks, leading to sharp signal fluctuations in adjacent regions that should ideally be smooth. Deblocking filters designed to mitigate this distortion are generally designed as low-pass filters that smooth out signal fluctuations. Since the amount of signal degradation varies depending on the coarseness of quantization, the filter strength is controlled by quantization parameters that define the coarseness of quantization (see, for example, Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Recommendation ITU-T H.265,(04 / 2013)“,High efficiency video coding”,International Telecommunication Union,April 2013 [Overview of the Initiative]

[0005] An encoding device according to one embodiment is an encoding device for encoding an input image, comprising: a transformation unit that performs an orthogonal transformation process on a residual image showing the difference between the input image and a predicted image of the input image to calculate orthogonal transformation coefficients; a quantization unit that generates quantization coefficients by quantizing the orthogonal transformation coefficients based on quantization parameters; an entropy encoding unit that generates encoded data by encoding the quantization coefficients; an image decoding unit that restores the orthogonal transformation coefficients from the quantization coefficients based on the quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients to restore the residual image, and adds the predicted image to generate a reconstructed image; and a deblocking filter unit that performs a filter process on the reconstructed image. The deblocking filter unit is characterized by controlling the filter intensity according to the luminance signal level of the reconstructed image and the quantization parameters.

[0006] A decoding device according to one embodiment is a decoding device for decoding encoded data of an input image, comprising: an entropy decoding unit that decodes the encoded data and obtains quantization coefficients obtained by quantizing the orthogonal transformation coefficients; an image decoding unit that restores the orthogonal transformation coefficients from the quantization coefficients based on quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients, and generates a reconstructed image by adding a predicted image to the restored residual image; and a deblocking filter unit that performs filtering on the reconstructed image. The deblocking filter unit is characterized by controlling the filter intensity according to the luminance signal level of the reconstructed image and the quantization parameters. [Brief explanation of the drawing]

[0007] [Figure 1] This diagram shows the correspondence between signal level and brightness level. [Figure 2] This is a block diagram showing an example configuration of an encoding device according to one embodiment of the present invention. [Figure 3] This figure shows the block boundaries that undergo deblocking filtering. [Figure 4]It is a block diagram showing a configuration example of a decoding device according to an embodiment of the present invention.

Embodiment for Carrying Out the Invention

[0008] As a feature of the new video media, the standardization of HDR (high dynamic range) signals with an expanded black-and-white expression range that cannot be expressed by conventional video signals has been carried out. In this HDR signal, compared with the conventional SDR (Standard Dynamic Range) signal, in order to record from where the light intensity is low to where it is high (that is, from dark to bright) within a limited bit depth, a signal suppression process called extreme gamma correction more than before is added. As HDR methods, currently, there are the HLG (Hybrid-Log Gamma) method defined in ARIB STD-B67 and the PQ (Perceptual Quantize) method defined in SMPTE ST.2084, and these methods have been internationally standardized as Recommendation ITU-R BT.2100 in ITU-R. Note that there is also a possibility that methods other than these will be defined in the future.

[0009] FIG. 1 shows the correspondence relationship (inverse gamma correction) between the luminance signal level of the image and the display luminance level displayed on the display device for the SDR signal and the HDR signals of the HLG method and the PQ method. Note that since the HLG method is a relative system with the peak luminance of the display device as the maximum value, in the figure, the peak luminance is shown as 1000 cd / m 2 Similarly, since the conventional SDR signal is also a relative system with the peak luminance of the display device as the maximum value, taking a currently commercially available display as an example, the peak luminance is shown as 250 cd / m 2

[0010] ​In an HDR signal, the change in the display luminance level (brightness) with respect to the variation in the luminance signal level is larger than that in a conventional SDR signal. Therefore, in a region with a large signal level, block noise due to quantization distortion is exaggerated and expressed compared to conventional signal degradation. In particular, in the PQ method with the highest signal suppression degree, the variation in the display luminance level with respect to the luminance signal level is remarkable, and the influence of signal degradation due to block distortion is also remarkable. In order to reduce this phenomenon, it is common practice to take measures to reduce the quantization parameter according to the signal level.

[0011] In a conventional deblocking filter, the threshold for switching the intensity of the filter for realizing smoothing between blocks is determined in advance according to the quantization parameter in units of frames, and control according to the luminance signal level has not been performed. Therefore, in an HDR signal, the non-linearity between the difference in the luminance signal level and the difference in the display luminance level is strong, and it has been difficult for the conventional deblocking filter to sufficiently reduce block distortion. Also, since there is non-linearity due to gamma correction even in a conventional SDR signal, there has been a problem that the effect of the deblocking filter is reduced in a region with a high luminance level.

[0012] Also, by making the quantization parameter smaller than necessary, it is possible to reduce the average error amount of the blocks. However, as the quantization parameter becomes smaller, the effect of the deblocking filter also becomes smaller, and it has not been possible to sufficiently improve the fact that the difference in the luminance signal level is remarkably displayed at the boundary. Also, there has been a problem that the compression effect is reduced because the amount of information increases when the quantization parameter is made smaller.

[0013] In view of such circumstances, an object of the present disclosure is to provide an encoding device, a decoding device, and a program capable of reducing block distortion for both the high luminance portion of an SDR signal and an HDR signal without impairing the compression effect.

[0014] An encoding device according to one embodiment is an encoding device for encoding an input image, comprising: a transformation unit that performs an orthogonal transformation on a residual image showing the difference between the input image and a predicted image of the input image to calculate orthogonal transformation coefficients; a quantization unit that generates quantization coefficients by quantizing the orthogonal transformation coefficients based on quantization parameters; an entropy encoding unit that generates encoded data by encoding the quantization coefficients; an image decoding unit that restores the orthogonal transformation coefficients from the quantization coefficients based on the quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients to restore the residual image, and adds the predicted image to generate a reconstructed image; and a deblocking filter unit that performs a filter operation on the reconstructed image. The deblocking filter unit controls the filter intensity according to the luminance signal level of the reconstructed image and the quantization parameters.

[0015] A decoding device according to one embodiment is a decoding device for decoding encoded data of an input image, comprising: an entropy decoding unit that decodes the encoded data and obtains quantization coefficients obtained by quantizing the orthogonal transformation coefficients; an image decoding unit that restores the orthogonal transformation coefficients from the quantization coefficients based on quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients, and generates a reconstructed image by adding a predicted image to the restored residual image; and a deblocking filter unit that performs filtering on the reconstructed image. The deblocking filter unit controls the filter intensity according to the luminance signal level of the reconstructed image and the quantization parameters.

[0016] With such encoding and decoding devices, the filter strength can be changed according to the luminance signal level, and block distortion can be reduced not only for SDR signals but also for HDR signals without impairing the compression effect.

[0017] One embodiment will be described in detail below with reference to the drawings. (encoding device) An encoding device according to one embodiment will be described below. Figure 2 shows an example of the configuration of the encoding device according to one embodiment. The encoding device 1 shown in Figure 2 includes a block division unit 11, a subtraction unit 12, a transformation unit 13, a quantization unit 14, an inverse quantization unit 15, an inverse transformation unit 16, an addition unit 17, a deblocking filter unit 18, a sample adaptive offset unit 19, a storage unit 20, an intra prediction unit 21, a motion compensation prediction unit 22, a switching unit 23, and an entropy encoding unit 24. Note that a processing unit that performs other post-filtering processing may be provided instead of or in addition to the sample adaptive offset unit 19.

[0018] The block division unit 11 divides the input image, which is the frame to be encoded, into multiple blocks and outputs the block images to the subtraction unit 12. The size of the blocks may be variable, for example, 32x32 pixels, 16x16 pixels, 8x8 pixels, or 4x4 pixels.

[0019] The subtraction unit 12 subtracts the pixel values ​​of the predicted image of the input image from the pixel values ​​of the block image input from the block division unit 11 to generate a residual image showing the difference between the block image and the predicted image, and outputs it to the conversion unit 13. The predicted image is input from the intra prediction unit 21 or the motion compensation prediction unit 22, which will be described later, via the switching unit 23.

[0020] The transformation unit 13 performs orthogonal transformation processing on the residual image input from the subtraction unit 12 to calculate orthogonal transformation coefficients, and outputs the orthogonal transformation coefficients for each block to the quantization unit 14.

[0021] The quantization unit 14 generates quantization coefficients by quantizing the orthogonal transformation coefficients for each block input from the transformation unit 13 based on a quantization parameter (qP) that defines the coarseness of quantization, and outputs the quantization coefficients to the inverse quantization unit 15 and the entropy coding unit 24. More specifically, the quantization unit 14 generates quantization coefficients by dividing the orthogonal transformation coefficients for each block input from the transformation unit 13 by the quantization step derived from the quantization parameter. For example, the value of the quantization parameter ranges from 0 to 51, and the quantization step doubles when the quantization parameter increases by 6 (i.e., the logarithm of the quantization parameter and the quantization step are proportional).

[0022] The inverse quantization unit 15 reconstructs the orthogonal transformation coefficients from the quantization coefficients input from the quantization unit 14 based on the quantization parameters and outputs them to the inverse transformation unit 16. More specifically, the inverse quantization unit 15 reconstructs the orthogonal transformation coefficients for each block by multiplying the quantization coefficients input from the quantization unit 14 by the quantization step derived from the quantization parameters.

[0023] The inverse transform unit 16 performs an inverse orthogonal transform on the orthogonal transform coefficients input from the inverse quantization unit 15 to generate a residual image, and outputs the generated residual image to the summing unit 17. For example, if the transformation unit 13 performs a discrete cosine transform, the inverse transform unit 16 performs an inverse discrete cosine transform.

[0024] The summing unit 17 adds the pixel values ​​of the residual image input from the inverse transform unit 16 and the predicted image input from the switching unit 23 to generate a reconstructed image, and outputs the reconstructed image to the deblocking filter unit 18.

[0025] The deblocking filter unit 18 performs filtering on the reconstructed image input from the summing unit 17 and outputs the filtered reconstructed image to the sample adaptive offset unit 19. The deblocking filter unit 18 controls the filter intensity according to the luminance signal level (pixel value of the luminance component) and quantization parameters of the reconstructed image. Details of this process will be described later.

[0026] The sample adaptive offset unit 19 classifies the image input from the deblocking filter unit 18 on a pixel-by-pixel basis, adds an offset corresponding to the classification to each pixel value, and outputs the result as a decoded image to the storage unit 20. The sample adaptive offset unit 19 also outputs the sample adaptive offset information to the entropy coding unit 24.

[0027] The intra-prediction unit 21 refers to the decoded image stored in the memory unit 20, performs intra-prediction to generate an intra-predicted image, and outputs the intra-predicted image to the switching unit 23. The intra-prediction unit 21 also outputs the selected intra-prediction mode to the entropy coding unit 24.

[0028] The motion compensation prediction unit 22 refers to the decoded image stored in the memory unit 20, generates motion vectors using methods such as block matching, and outputs the motion vector information to the entropy coding unit 24. Furthermore, the motion compensation prediction unit 22 generates a motion compensation prediction image based on the motion vectors and outputs the motion compensation prediction image to the switching unit 23.

[0029] The switching unit 23 switches between the intra-prediction image input from the intra-prediction unit 21 and the motion-compensated prediction image input from the motion-compensated prediction unit 22, and outputs the predicted image of the decoded image (intra-prediction image or motion-compensated prediction image) to the subtraction unit 12 and the addition unit 17.

[0030] The image decoding unit 10 is comprised of an inverse quantization unit 15, an inverse transformation unit 16, an addition unit 17, an intra prediction unit 21, a motion compensation prediction unit 22, and a switching unit 23. As described above, the image decoding unit 10 reconstructs orthogonal transformation coefficients from quantization coefficients based on quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients, and generates a reconstructed image by adding a predicted image to the reconstructed residual image.

[0031] The entropy coding unit 24 performs entropy coding on the quantization coefficients input from the quantization unit 14, the intra-prediction mode input from the intra-prediction unit 21, the predicted motion vector information input from the motion compensation prediction unit 22, the filter information input from the deblocking filter unit 18, and the sample adaptive offset information input from the sample adaptive offset unit 19. It then compresses the data to generate coded data and outputs the coded data to the outside of the coding device 1. Any entropy coding scheme can be used for entropy coding, such as zero-order exponential Golomb coding or CABAC (Context-based Adaptive Binary Arithmetic Coding).

[0032] (Deblocking filter section) Next, the details of the deblocking filter unit 18 will be described. In this embodiment, the block size processed by the deblocking filter unit 18 is, for example, 8 x 8 pixels. The deblocking filter unit 18 first determines a boundary strength Bs value, which indicates the strength of the smoothing process for each block. The Bs value is set to one of 0, 1, or 2.

[0033] Figure 3 shows the block boundaries for deblocking filtering. Referring to Figure 3, an example of deblocking filtering compliant with the H.265 / HEVC scheme will be explained. If block P or Q is a block that performs intra prediction, the Bs value is set to 2. If blocks P and Q are blocks that perform inter prediction and satisfy at least one of the following conditions, the Bs value is set to 1; otherwise, the Bs value is set to 0. Block P or Q contains significant (non-zero) orthogonal transformation coefficients and is a boundary of the Transform Unit (TU). • The number of motion vectors or reference images for blocks P and Q are different. The absolute value of the difference between the motion vectors of blocks P and Q must be 4 pixels or more.

[0034] When the Bs value is 0, the deblocking filter unit 18 does not perform filter processing. Hereinafter, taking the vertical block boundary shown in FIG. 3 as an example, the description will be given. When the Bs value is 1 or 2, the filtering process is performed only when the following equation (1) is satisfied.

[0035]

Equation

[0036] When performing the filtering process, the deblocking filter unit 18 applies a strong filter when all of the following conditional expressions (2) to (7) are satisfied, and applies a weak filter in other cases.

[0037]

Equation

[0038] Threshold values β and t C The values of are changed according to the average value Q av of the quantization parameters of the adjacent blocks P and Q. The deblocking filter unit 18 has a reference table showing the correspondence between Q av and the threshold values β and t C . An example of the reference table is shown in Table 1. When the bit depth of the image is 8 bits, the threshold values β and t C are denoted as threshold values β’ and t C ’ respectively. Note that Q av , β’, and t C ’ can also be values obtained by adding offsets in units of frames or slices respectively.

[0039]

Table 1

[0040] Assuming that the bit depth is B, the threshold values β and t C are represented by equations (8) and (9) respectively. Here, <<1 means an arithmetic left shift operation of 1 bit.

[0041]

number

[0042] In this invention, the deblocking filter unit 18 shifts the reference table by the newly added luminance signal level (pixel value of the luminance component) L to set the threshold β and t C Set the following. The value of the luminance signal level L is, for example, (p00+p03+q00+q03) / 4 or (p00+p01+p02+p03+q00+q01+q02+q03) / 8. Note that the method for determining the luminance signal level L is just one example and is not limited to this.

[0043] The deblocking filter unit 18 acquires a format that defines the dynamic range of the luminance values ​​of the input image. Regarding the video format, for example, in the H.265 / HEVC method, it is transmitted using a high-level syntax called a Sequence parameter set, and it is generally possible for the decoding device to identify the type of signal. In this embodiment, this format is one of three types: SDR, HLG, and PQ. Considering that HDR methods such as PQ and HLG have a significantly greater impact on display luminance due to differences in luminance signal levels compared to the SDR method, the deblocking filter unit 18 controls the filter strength according to the luminance signal level L. Specifically, β' and t shown in Table 1 are used. C ' to, Q av β'[Q] is the index av ] and t C '[Q av ] and the threshold β'[Q av -a] and t C '[Q av-b] is controlled by shift amounts a and b. Shift amounts a and b are determined, for example, by the criterion in equation (10). Equation (10) shows an example of shift amounts a and b when the luminance signal level L is normalized to 0 to 1.0. The deblocking filter unit 18 may also determine shift amounts a and b according to the requirements of each application, or simply a = b. Alternatively, a = 0 or b = 0, and the thresholds β', t C You can also choose to shift only one of the ' characters. In the case of SDR signals if (L < 0.75) a=0; else if (L >= 0.75) a=2; if (L < 0.75) b = 0; else if (L >= 0.75) b=1; In the case of HLG signals if (L < 0.5) a=0; else if (L >= 0.5 && L < 0.75) a=2; else if (L >= 0.75) a=5; if (L < 0.5) b = 0; else if (L >= 0.5 && L < 0.7) bgar3; else if (L >= 0.7) b = 6; In the case of a PQ signal if (L < 0.3) a = -1; else if (L >= 0.3 && L < 0.4) a=0; else if (L >= 0.4 && L < 0.5) a=1; else if (L >= 0.5 && L < 0.7) a=5; else if (L >= 0.7 && L < 0.85) a=10; else if (L >= 0.85 && L < 0.95) a=12; else if (L >= 0.95) a=15; if (L < 0.3) b = -1; else if (L >= 0.3 && L < 0.5) b = 0; else if (L >= 0.5 && L < 0.7) b=1; else if (L >= 0.7 && L < 0.95) b=5; else if (L >= 0.95) b=7; (10)

[0044] For example, when the shift amount a=b=5, the deblocking filter unit 18 uses the threshold β' and t of the reference table. C Shift ' to the left by 5 units. The results are shown in Table 2. Note that if the shift amount a is negative, it is shifted to the right. Note that the threshold β' and t are as shown in the table. C If ' becomes 0, the lower limit of the thresholds thereafter will also be set to 0. Threshold β' and t C If the value reaches the upper limit of 64 or 24, the value thereafter will be capped at the upper limit.

[0045] [Table 2]

[0046] The deblocking filter unit 18 adjusts the threshold β' and t of the reference table according to the shift amount a defined according to the luminance signal level L. C By shifting ', Q av The threshold for switching the filter intensity can be adaptively controlled according to the following criteria: The thresholds β' and t in the reference table. CShifting ' to the right gives threshold β and t C As the value of increases, the above conditions (2) to (7) become easier to satisfy, and a stronger filter is more likely to be applied. Therefore, in the encoding device 1 according to the present invention, when the luminance signal level L is large, a stronger filter is more likely to be applied in the deblocking filter section 18, and as a result, the occurrence of block distortion can be reduced without impairing the compression effect.

[0047] Thus, in the encoding device 1, the deblocking filter unit 18 controls the filter intensity according to the luminance signal level and quantization parameters of the reconstructed image. In one embodiment, the deblocking filter unit 18 controls the first value (Q) calculated from the quantization parameters. av ) and the second value (β, t) that determines the filter strength C The deblocking filter unit 18 maintains filter intensity setting information (reference table) that shows the correspondence with the first value. The deblocking filter unit 18 modifies the filter intensity setting information according to the luminance signal level of the reconstructed image and derives a second value by applying the first value to the modified filter intensity setting information. The first value is determined by the average value of the quantization parameters of two adjacent blocks in the reconstructed image. The second value is a value that functions as a threshold for switching the filter intensity. The deblocking filter unit 18 switches the filter intensity using the second value.

[0048] In one embodiment, the deblocking filter unit 18 controls the filter intensity according to a format that defines the dynamic range of the luminance values ​​of the input image. The deblocking filter unit 18 uses a first value (Q) calculated from the quantization parameter. av ) and the second value (β, t) that determines the filter strength CThe deblocking filter unit 18 holds filter intensity setting information (reference table) that shows the correspondence with ) and correction information (see equation (10)) that defines a method for correcting the filter intensity setting information for each format. The deblocking filter unit 18 identifies a correction method corresponding to the format applied to the input image based on the correction information, corrects the filter intensity setting information according to the luminance signal level of the reconstructed image using the identified correction method, and derives a second value by applying a first value to the corrected filter intensity setting information.

[0049] Furthermore, a computer can be suitably used to function as the encoding device 1 described above. Such a computer can be realized by storing a program in its memory that describes the processing content for realizing each function of the encoding device 1, and by having the computer's CPU read and execute this program. This program can be recorded on a computer-readable recording medium.

[0050] (Decryption device) Next, a decoding device according to one embodiment will be described. Figure 4 is a block diagram showing an example configuration of a decoding device according to one embodiment. The decoding device 2 shown in Figure 4 includes an entropy decoding unit 31, an inverse quantization unit 32, an inverse transformation unit 33, an addition unit 34, a deblocking filter unit 35, a sample adaptive offset unit 36, a storage unit 37, an intra prediction unit 38, a motion compensation prediction unit 39, and a switching unit 40. The decoding device 2 decodes the encoded data of the input image encoded by the encoding device 1.

[0051] The entropy decoding unit 31 decodes the encoded data output by the encoding device 1 and obtains quantization coefficients, intra-prediction mode, motion prediction information, filter information, and sample adaptive offset information. The entropy decoding unit 31 then outputs the quantization coefficients to the inverse quantization unit 32, the intra-prediction mode to the intra-prediction unit 38, the motion prediction information to the motion compensation prediction unit 39, the filter information to the deblocking filter unit 35, and the sample adaptive offset information to the sample adaptive offset unit 36.

[0052] The inverse quantization unit 32 receives the quantization coefficients and quantization parameters from the entropy decoding unit 31, multiplies the quantization coefficients by the quantization step derived from the quantization parameters to reconstruct the orthogonal transformation coefficients for each block, and outputs the orthogonal transformation coefficients to the inverse transformation unit 33.

[0053] The inverse transform unit 33 performs an inverse transform on the orthogonal transform coefficients input from the inverse quantization unit 32 to generate a residual image, and outputs the residual image to the adder unit 34.

[0054] The summing unit 34 adds the pixel values ​​of the residual image input from the inverse transform unit 33 and the predicted image input from the switching unit 40 to generate a reconstructed image, and outputs the reconstructed image to the deblocking filter unit 35.

[0055] The deblocking filter unit 35 performs filtering on the reconstructed image input from the summing unit 34 and outputs the filtered reconstructed image to the sample adaptive offset unit 36. The deblocking filter unit 35 controls the filter intensity according to the luminance signal level (pixel value of the luminance component) and quantization parameters of the reconstructed image.

[0056] The sample adaptive offset unit 36 ​​adds an offset to the image input from the deblocking filter unit 35 according to the sample adaptive offset information input from the entropy decoding unit 31, and outputs the result as a decoded image to the storage unit 37.

[0057] The memory unit 37 stores one frame of image and outputs the stored image to the outside of the decoding device 2.

[0058] The intra-prediction unit 38 refers to the decoded image stored in the memory unit 37, performs prediction processing according to the intra-prediction mode input from the entropy decoding unit 31 to generate an intra-prediction image, and outputs the intra-prediction image to the switching unit 40.

[0059] The motion compensation prediction unit 39 refers to the decoded image stored in the memory unit 37, performs prediction processing according to the motion vector information input from the entropy decoding unit 31 to generate a motion compensation prediction image, and outputs the motion compensation prediction image to the switching unit 40.

[0060] The switching unit 40 switches between the intra-prediction image input from the intra-prediction unit 38 and the motion-compensated prediction image input from the motion-compensated prediction unit 39, and outputs either the intra-prediction image or the motion-compensated prediction image to the summing unit 34.

[0061] The image decoding unit 30 is comprised of an inverse quantization unit 32, an inverse transformation unit 33, an addition unit 34, an intra prediction unit 38, a motion compensation prediction unit 39, and a switching unit 40. As described above, the image decoding unit 30 reconstructs orthogonal transformation coefficients from quantization coefficients based on quantization parameters, performs an inverse orthogonal transformation on the orthogonal transformation coefficients, and generates a reconstructed image by adding the predicted image of the decoded image to the reconstructed residual image.

[0062] The processing of the deblocking filter unit 35 is the same as that of the deblocking filter unit 18. That is, the deblocking filter unit 35 processes the threshold β' and t of the reference table according to the shift amount a defined according to the luminance signal level L. C By shifting ', Q av The threshold for switching the filter intensity can be adaptively controlled according to the following criteria: The thresholds β' and t in the reference table. C Shifting ' to the right gives threshold β and t CAs the value of increases, the above conditions (2) to (7) become easier to satisfy, and a stronger filter is more easily applied. Therefore, in the decoding device 2 according to the present invention, when the luminance signal level L is large, a stronger filter is more easily applied in the deblocking filter section 35, and as a result, the occurrence of block strain can be reduced without impairing the compression effect.

[0063] Thus, in the decoding device 2, the deblocking filter unit 35 controls the filter intensity according to the luminance signal level and quantization parameters of the reconstructed image. In one embodiment, the deblocking filter unit 35 controls the first value (Q) calculated from the quantization parameters. av ) and the second value (β, t) that determines the filter strength C The deblocking filter unit 35 maintains filter intensity setting information (reference table) that shows the correspondence with the first value. The deblocking filter unit 35 modifies the filter intensity setting information according to the luminance signal level of the reconstructed image and derives a second value by applying the first value to the modified filter intensity setting information. The first value is a value determined by the average value of the quantization parameters of two adjacent blocks in the reconstructed image. The second value is a value that functions as a threshold for switching the filter intensity. The deblocking filter unit 35 switches the filter intensity using the second value.

[0064] In one embodiment, the deblocking filter unit 35 controls the filter intensity according to a format that defines the dynamic range of the luminance values ​​of the input image. The deblocking filter unit 35 holds filter intensity setting information (reference table) that shows the correspondence between a first value calculated from quantization parameters and a second value that determines the filter intensity, and correction information (see equation (10)) that defines a method for correcting the filter intensity setting information for each format. The deblocking filter unit 35 identifies a correction method corresponding to the format applied to the input image based on the correction information, corrects the filter intensity setting information according to the luminance signal level of the reconstructed image using the identified correction method, and derives a second value by applying the first value to the corrected filter intensity setting information.

[0065] Furthermore, a computer can be suitably used to function as the decoding device 2 described above. Such a computer can be realized by storing a program in its memory that describes the processing content for realizing each function of the decoding device 2, and having the computer's CPU read and execute this program. This program can be recorded on a computer-readable recording medium.

[0066] Although the embodiments described above are representative examples, it will be apparent to those skilled in the art that many modifications and substitutions are possible within the spirit and scope of the present invention. Therefore, the present invention should not be interpreted as being limited by the embodiments described above, and various modifications and changes are possible without departing from the scope of the claims. For example, it is possible to combine multiple component blocks shown in the configuration diagram of the embodiments into one, or to divide one component block.

[0067] This application claims priority to Japanese Patent Application No. 2016-230524 (filed November 28, 2016) and Japanese Patent Application No. 2017-23345 (filed February 10, 2017), and all of their contents are incorporated into the specification of this application. [Explanation of symbols]

[0068] 1 Encoding device 2 Decoder 10 Image decoding unit 11 Block division section 12 Subtraction Unit 13 Conversion section 14 Quantization section 15 Inverse quantization section 16 Inverse Transform Section 17 Addition section 18 Deblocking filter section 19 Sample Adaptive Offset Section 20 Memory section 21 Intra Prediction Unit 22 Motion Compensation Prediction Unit 23 Switching section 24 Entropy coding unit 30 Image Decoding Unit 31 Entropy Decoder 32 Inverse quantization section 33 Inverse Transform Section 34 Addition section 35 Deblocking filter section 36 Sample Adaptive Offset Section 37 Memory section 38 Intra Prediction Unit 39 Motion Compensation Prediction Unit 40 Switching section

Claims

1. A decoding device, The system includes an acquisition means for obtaining a bitstream that includes quantization coefficients obtained by quantizing the transformation coefficients of blocks obtained by dividing an image, and a sequence parameter set which is a high-level syntax. The decoding device uses the sequence parameter set acquired by the acquisition means to set one or more thresholds to be used for deblocking filtering of the block. The decoding device generates a reconstructed image using the quantization coefficient acquired by the acquisition means. The decoding device uses the sequence parameter set acquired by the acquisition means to set one or more thresholds, thereby identifying the luminance signal level range to which the luminance signal level belongs, and uses the adjustment values ​​associated with the identified luminance signal level range to determine the parameters for controlling the deblocking filter process. Decoding device.

2. The computer is made to function as the decoding device described in claim 1. program.

Images