JP6903778B2 - Storage device, transmitter and receiver - Google Patents

Description

Embodiments of the present invention relate to storage devices, transmitters, receivers and coded data.

In recent years, an image coding method with significantly improved coding efficiency has been developed in collaboration with ITU-T (International Telecommunication Union Telecommunication Standardization Sector) and ISO (International Organization for Standardization) / IEC (International Electrotechnical Commission). T REC. H. It is recommended as 264 and ISO / IEC 14496-10 (hereinafter referred to as "H.264").

H. 264 discloses an inter-prediction coding method that eliminates redundancy in the time direction and realizes high coding efficiency by performing motion compensation prediction with fractional accuracy using a coded image as a reference image. ing.

In addition, a method for encoding moving images including fade and dissolve effects with higher efficiency than the inter-prediction coding method in ISO / IEC MPEG (Moving Picture Experts Group) -1,2,4 has also been proposed. In this method, as a framework for predicting a change in brightness in the time direction, motion compensation prediction with fractional accuracy is performed for an input moving image having brightness and two color differences. Then, the predicted image is multiplied by the weighting coefficient and the offset is added by using the reference image, the luminance and the weighting coefficient for each of the two color differences, and the luminance and the offset for each of the two color differences. The weighting coefficient can express a fractional value with a predetermined accuracy by a parameter indicating fixed-point accuracy, and it becomes possible to perform weighted motion compensation prediction with a finer accuracy for a pixel value change between images. There is.

Japanese Unexamined Patent Publication No. 2004-7377

In the conventional technique as described above, the reference image, the weighting coefficient, the offset, and the like are encoded as an index, but since the index is specified to be expressed with a predetermined bit precision, the weighting coefficient cannot be expressed. There is. An object to be solved by the present invention is to provide an electronic device, a decoding method and a program capable of improving coding efficiency while being able to express a weighting coefficient with a predetermined bit accuracy.

The coding method of the embodiment is the same value as the step of encoding the first fixed-point precision of the brightness weighting coefficient, the difference between the first fixed-point precision and the second fixed-point precision of the color difference weighting coefficient. A step of encoding a first difference value, a first reference value which is the same value as a value obtained by shifting "1" to the left by the number of bits determined by the first fixed-point precision, and the brightness. Includes a step of encoding a second difference value of the brightness weighting factor, which is the same value as the difference between the weighting factors of.

The block diagram which shows the example of the coding apparatus of 1st Embodiment. The explanatory view which shows the predictive coding order example of the pixel block of 1st Embodiment. Explanatory drawing which shows another example of the predictive coding order of the pixel block of 1st Embodiment. The figure which shows the block size example of the coding tree block in 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The block diagram which shows the example of the prediction image generation part of 1st Embodiment. The figure which shows the example of the relationship of the motion vector of the motion compensation prediction in the bidirectional prediction of the first embodiment. The block diagram which shows the example of the multi-frame motion compensation part of 1st Embodiment. Reference diagram for explaining the weighting factor. H. The reference figure which shows the selection range of the weighting coefficient of 264. The explanatory view which shows the example of the selection range of the weighting coefficient of 1st Embodiment. The explanatory view which shows the specific example of the selection range of the weighting coefficient of 1st Embodiment. The explanatory view which shows the specific example of the selection range of the weighting coefficient of 1st Embodiment. H. The reference figure which shows the minimum value and the maximum value of the weighting coefficient of 264. The explanatory view which shows the example of the minimum value and the maximum value of the weighting coefficient of 1st Embodiment. The figure which shows the example of WP parameter information of 1st Embodiment. The figure which shows the example of WP parameter information of 1st Embodiment. The flowchart which shows the derivation processing example of the selection range of the weighting coefficient of 1st Embodiment. The figure which shows the example of the syntax of 1st Embodiment. The figure which shows the example of the picture parameter set syntax of 1st Embodiment. The figure which shows the example of the slice header syntax of 1st Embodiment. The figure which shows the example of the pred weight table syntax of 1st Embodiment. The explanatory view which shows the example of the relationship of the value of the syntax element of 1st Embodiment. The block diagram which shows the structural example of the decoding apparatus of 2nd Embodiment. The explanatory view which shows the example of the offset selection range of the modification 1. The flowchart which shows the derivation processing example of the offset selection range of the modification 1. The explanatory view which shows the example of the selection range of the weighting coefficient of the modification 2. The flowchart which shows the derivation processing example of the selection range of the weighting coefficient of modification 2. The explanatory view which shows the example of the range of the difference value of the weighting coefficient of the coded object of the modification 3. The explanatory view which shows the example of the relationship of the value of the syntax element of the modification 3. The explanatory view which shows the example of the range of the difference value of the weighting coefficient of the modification 4. The explanatory view which shows the example of the selection range of the weighting coefficient after decoding of the modification 4. The flowchart which shows the wrap processing example of the difference value of the weighting coefficient of the modification 5. The flowchart which shows the restoration processing example of the difference value of the weighting coefficient of the modification 5.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. The coding device and decoding device of each of the following embodiments can be realized by hardware such as an LSI (Large-Scale Integration) chip, a DSP (Digital Signal Processor), or an FPGA (Field Programmable Gate Array). Further, the coding device and the decoding device of each of the following embodiments can be realized by causing a computer to execute a program, that is, by software. In the following description, the term "image" can be appropriately read as a term such as "video", "pixel", "image signal", "picture", or "image data".

(First Embodiment)
In the first embodiment, a coding device that encodes a moving image will be described.

FIG. 1 is a block diagram showing an example of the configuration of the coding device 100 of the first embodiment.

The coding device 100 divides each frame or each field constituting the input image into a plurality of pixel blocks, and uses the coding parameters input from the coding control unit 111 to obtain a predictive code for the divided pixel blocks. And generate a predicted image. Then, the coding apparatus 100 generates a prediction error by subtracting the input image divided into a plurality of pixel blocks and the prediction image, and the generated prediction error is orthogonally converted and quantized, and further subjected to entropy coding for coding. Generate and output data.

The coding device 100 selectively applies a plurality of prediction modes in which at least one of the block size of the pixel block and the method of generating the prediction image is different to perform prediction coding. There are roughly two types of prediction image generation methods: intra-prediction, which makes predictions within a coded frame, and inter-prediction, which makes motion compensation predictions using one or more reference frames that differ in time. Intra-prediction is also referred to as in-screen prediction or in-frame prediction, and inter-prediction is also referred to as inter-screen prediction, inter-frame prediction, motion compensation prediction, or the like.

FIG. 2A is an explanatory diagram showing an example of the predicted coding order of the pixel blocks in the first embodiment. In the example shown in FIG. 2A, the coding device 100 performs predictive coding from the upper left to the lower right of the pixel block, and in the frame f to be coded, the left side and the left side of the pixel block c to be coded. The coded pixel block p is located on the upper side.

FIG. 2B is an explanatory diagram showing another example of the predicted coding order of the pixel blocks in the first embodiment. In the example shown in FIG. 2B, the coding device 100 divides the screen into a plurality of tiles or slices in advance, and then predictively encodes the pixel blocks in each tile or each slice from the upper left to the lower right. In the frame f to be coded, the coded pixel block p is located on the left side and the upper side of the pixel block c to be coded. The tile means an area cut out from the screen by an arbitrary rectangular area, and the slice means an area cut out by an arbitrary number of large coding tree blocks described later according to the predicted coding order.

As in the example shown in FIG. 2B, after the screen is divided into a plurality of tiles or a plurality of slices, the coding process is performed for each tile or each slice, so that the decoding process for each tile or each slice is possible. Become. Therefore, by performing the decoding processing of the high-resolution video in parallel, it is possible to disperse the amount of calculation required for decoding. That is, in the case of the example shown in FIG. 2B, the coding process and the decoding process can be speeded up.

In the following, for simplification of the description, the coding apparatus 100 shall perform predictive coding in the order shown in FIG. 2A, but the order of predictive coding is not limited to this.

The pixel block indicates a unit for processing an image, and corresponds to, for example, an M × N size block (M and N are natural numbers), a coding tree block, a macro block, a sub block, or one pixel. In the following description, the pixel block is basically used in the meaning of a coding tree block, but it may be used in other meanings. For example, in the description of the prediction unit, the pixel block is used to mean the pixel block of the prediction unit. In addition, the block is sometimes called by a name such as a unit. For example, a coding block is called a coding unit.

FIG. 3A is a diagram showing an example of the block size of the coding tree block according to the first embodiment. The coding tree block is typically a 64x64 pixel block as shown in FIG. 3A. However, the present invention is not limited to this, and may be a 32 × 32 pixel block, a 16 × 16 pixel block, an 8 × 8 pixel block, a 4 × 4 pixel block, or the like. Further, the coding tree block does not have to be a square, and may be, for example, a pixel block of M × N size (M ≠ N).

3B to 3D are diagrams showing specific examples of the coding tree block of the first embodiment. FIG. 3B shows a coding tree block with a block size of 64 × 64 (N = 32). N represents the size of the reference coding tree block, and the size when divided is N and the size when not divided is 2N. FIG. 3C shows a coding tree block obtained by dividing the coding tree block of FIG. 3B into quadtrees. The coding tree block has a quadtree structure, as shown in FIG. 3C. When the coding tree block is divided, the four pixel blocks after the division are numbered in the Z scan order as shown in FIG. 3C.

The coding tree block can be further divided into quadtrees within the number of one quadtree. This makes it possible to divide the coding tree block hierarchically. In this case, the depth of division is defined by Depth. FIG. 3D shows one of the coding tree blocks obtained by dividing the coding tree block of FIG. 3B into quadtrees, and the block size is 32 × 32 (N = 16). The Depth of the coding tree block shown in FIG. 3B is 0, and the Depth of the coding tree block shown in FIG. 3D is 1. The coding tree block having the largest unit is called a large coding tree block, and the input image signal is encoded in the raster scan order in this unit.

In the following description, the coding target block or coding tree block of the input image may be referred to as a prediction target block or a prediction pixel block. The coding unit is not limited to the pixel block, and at least one of a frame, a field, a slice, a line, and a pixel can be used.

As shown in FIG. 1, the coding apparatus 100 predicts that the subtraction unit 101, the orthogonal transform unit 102, the quantization unit 103, the inverse quantization unit 104, the inverse orthogonal transform unit 105, and the addition unit 106. An image generation unit 107, an index setting unit 108, a motion evaluation unit 109, and a coding unit 110 are provided. The coding control unit 111 shown in FIG. 1 controls the coding device 100, and can be realized by, for example, a CPU (Central Processing Unit) or the like.

The subtraction unit 101 subtracts the corresponding prediction image from the input image divided into pixel blocks to obtain a prediction error. The subtraction unit 101 outputs a prediction error and inputs it to the orthogonal transform unit 102.

The orthogonal transform unit 102 performs an orthogonal transform such as a discrete cosine transform (DCT) or a discrete sine transform (DST) on the prediction error input from the subtraction unit 101 to obtain a conversion coefficient. The orthogonal transform unit 102 outputs the conversion coefficient and inputs it to the quantization unit 103.

The quantization unit 103 performs a quantization process on the conversion coefficient input from the orthogonal transformation unit 102 to obtain a quantization conversion coefficient. Specifically, the quantization unit 103 performs quantization according to quantization information such as a quantization parameter and a quantization matrix specified by the coding control unit 111. More specifically, the quantization unit 103 divides the conversion coefficient by the quantization step size derived from the quantization information to obtain the quantization conversion coefficient. The quantization parameter indicates the fineness of quantization. The quantization matrix is used to weight the quantization fineness for each component of the conversion factor. The quantization unit 103 outputs the quantization conversion coefficient and inputs it to the inverse quantization unit 104 and the coding unit 110.

The inverse quantization unit 104 performs an inverse quantization process on the quantization conversion coefficient input from the quantization unit 103 to obtain a restoration conversion coefficient. Specifically, the inverse quantization unit 104 performs inverse quantization according to the quantization information used in the quantization unit 103. More specifically, the inverse quantization unit 104 multiplies the quantization step size derived from the quantization information by the quantization conversion coefficient to obtain the restoration conversion coefficient. The quantization information used in the quantization unit 103 is loaded from an internal memory (not shown) of the coding control unit 111 and used. The inverse quantization unit 104 outputs the restoration conversion coefficient and inputs it to the inverse orthogonal transformation unit 105.

The inverse orthogonal transform unit 105 performs an inverse orthogonal transform such as an inverse discrete cosine transform (IDCT) or an inverse discrete sine transform (IDST) on the restoration transform coefficient input from the inverse quantize unit 104. Obtain the restoration prediction error. The inverse orthogonal transform performed by the inverse orthogonal transform unit 105 corresponds to the orthogonal transform performed by the orthogonal transform unit 102. The inverse orthogonal transform unit 105 outputs the restoration prediction error and inputs it to the addition unit 106.

The addition unit 106 adds the restoration prediction error input from the inverse orthogonal transform unit 105 and the corresponding prediction image to generate a locally decoded image. The addition unit 106 outputs a locally decoded image and inputs it to the prediction image generation unit 107.

The prediction image generation unit 107 stores the locally decoded image input from the addition unit 106 as a reference image in a memory (not shown in FIG. 1), outputs the reference image stored in the memory, and inputs the reference image to the motion evaluation unit 109. .. Further, the prediction image generation unit 107 performs weighted motion compensation prediction based on the motion information and WP parameter information input from the motion evaluation unit 109, and generates a prediction image. The prediction image generation unit 107 outputs a prediction image and inputs it to the subtraction unit 101 and the addition unit 106.

FIG. 4 is a block diagram showing an example of the configuration of the prediction image generation unit 107 of the first embodiment. As shown in FIG. 4, the prediction image generation unit 107 includes a plurality of frame motion compensation unit 201, a memory 202, a unidirectional motion compensation unit 203, a prediction parameter control unit 204, a reference image selector 205, and a frame memory 206. And a reference image control unit 207.

The frame memory 206 stores the locally decoded image input from the addition unit 106 as the reference image under the control of the reference image control unit 207. The frame memory 206 has a plurality of memory sets FM1 to FMN (N ≧ 1) for temporarily holding the reference image.

The prediction parameter control unit 204 prepares a plurality of combinations of the reference image number and the prediction parameter as a table based on the movement information input from the motion evaluation unit 109. Here, the motion information refers to a motion vector indicating the amount of motion deviation used in motion compensation prediction, a reference image number, information on a prediction mode such as unidirectional / bidirectional prediction, and the like. Prediction parameters refer to information about motion vectors and prediction modes. Then, the prediction parameter control unit 204 selects and outputs a combination of the reference image number and the prediction parameter used for generating the prediction image based on the input image, inputs the reference image number to the reference image selector 205, and inputs the prediction parameter. Is input to the unidirectional motion compensation unit 203.

The reference image selector 205 is a switch that switches which output terminal of the frame memories FM1 to FMN of the frame memory 206 is connected according to the reference image number input from the prediction parameter control unit 204. For example, if the reference image number is 0, the reference image selector 205 connects the output end of the FM1 to the output end of the reference image selector 205, and if the reference image number is N-1, the reference image selector 205 refers to the output end of the FMN. Connect to the output end of the image selector 205. The reference image selector 205 outputs a reference image stored in the frame memory to which the output end is connected among the frame memories FM1 to FMN of the frame memory 206, and outputs the unidirectional motion compensation unit 203 and the motion evaluation unit 109. Enter in.

The unidirectional motion compensation unit 203 performs motion compensation prediction processing according to the prediction parameters input from the prediction parameter control unit 204 and the reference image input from the reference image selector 205, and generates a unidirectional prediction image.

FIG. 5 is a diagram showing an example of the relationship between the motion vectors of the motion compensation prediction in the bidirectional prediction of the first embodiment. In motion compensation prediction, interpolation processing is performed using the reference image, and a unidirectional prediction image is generated based on the amount of movement deviation from the pixel block of the coded target position between the created interpolation image and the input image. .. Here, the amount of deviation is a motion vector. As shown in FIG. 5, in the bidirectional prediction slice (B-slice), a prediction image is generated using two types of reference images and a set of motion vectors. As the interpolation process, an interpolation process with 1/2 pixel accuracy, an interpolation process with 1/4 pixel accuracy, or the like is used, and the value of the interpolated image is generated by performing the filtering process on the reference image. For example, H.I. In 264, the amount of deviation is expressed as four times the precision of the integer pixel.

The unidirectional motion compensation unit 203 outputs a unidirectional prediction image and temporarily stores it in the memory 202. Here, when the motion information (prediction parameter) indicates bidirectional prediction, the multi-frame motion compensation unit 201 performs weighted prediction using two types of unidirectional prediction images, so that the unidirectional motion compensation unit 203 The first unidirectional prediction image corresponding to the first is stored in the memory 202, and the unidirectional prediction image corresponding to the second is directly output to the multi-frame motion compensation unit 201. Here, the unidirectional prediction image corresponding to the first is referred to as the first prediction image, and the unidirectional prediction image corresponding to the second is referred to as the second prediction image.

It should be noted that two unidirectional motion compensation units 203 may be prepared, and each may generate two unidirectional prediction images. In this case, when the motion information (prediction parameter) indicates unidirectional prediction, the unidirectional motion compensation unit 203 may directly output the first unidirectional prediction image as the first prediction image to the multi-frame motion compensation unit 201. Good.

The multi-frame motion compensation unit 201 uses the first prediction image input from the memory 202, the second prediction image input from the unidirectional motion compensation unit 203, and the WP parameter information input from the motion evaluation unit 109. A weighted prediction is performed to generate a prediction image. The multi-frame motion compensation unit 201 outputs a predicted image and inputs it to the subtraction unit 101 and the addition unit 106.

FIG. 6 is a block diagram showing an example of the configuration of the multi-frame motion compensation unit 201 of the first embodiment. As shown in FIG. 6, the multi-frame motion compensation unit 201 includes a default motion compensation unit 301, a weighted motion compensation unit 302, a WP parameter control unit 303, and WP selectors 304 and 305.

The WP parameter control unit 303 outputs the WP application flag and weight information based on the WP parameter information input from the motion evaluation unit 109, inputs the WP application flag to the WP selectors 304 and 305, and weights the weight information. Input to the motion compensation unit 302. Specifically, when the WP parameter information is input from the motion evaluation unit 109, the WP parameter control unit 303 separates the WP parameter information into a first WP application flag, a second WP application flag, and weight information and outputs the information. Then, the first WP application flag is input to the WP selector 304, the second WP application flag is input to the WP selector 305, and the weight information is input to the weighted motion compensation unit 302.

Here, the WP parameter information includes a first WP application flag (specifically, flag information of the first WP application flag), a second WP adaptation flag (specifically, flag information of the second WP application flag), and a weight. Includes informational information. The first WP application flag and the second WP application flag are parameters that can be set for each corresponding reference image and signal component, and whether to perform default motion compensation prediction for the prediction of the first prediction image and the second prediction image, respectively. Contains information on whether to make weighted motion compensation predictions. Here, it is assumed that the first WP application flag and the second WP application flag both indicate that the default motion compensation prediction is performed when it is 0, and that the weighted motion compensation prediction is performed when it is 1. ..

The weight information is a parameter LWD indicating the value w0C of the first weighting coefficient, the value w1C of the second weighting coefficient, the fixed-point accuracy of the first weighting coefficient and the second weighting coefficient (hereinafter, may be referred to as "fixed-point precision LWD"). Includes information on), first offset o0C, and second offset o1C. The variable C means a signal component. For example, in the case of a YUV spatial signal, the luminance signal is represented by C = Y, the Cr color difference signal is represented by C = Cr, and the Cb color difference component is represented by C = Cb.

The first weighting coefficient is a weighting coefficient corresponding to the first predicted image, and is a parameter whose value is determined (varies) by the fixed-point precision LWD. The second weighting coefficient is a weighting coefficient corresponding to the second predicted image, and is a parameter whose value is determined (varies) by the fixed-point precision LWD. The fixed-point precision LWD is a parameter that controls the step size corresponding to the fractional precision of the first weighting factor and the second weighting factor. The fixed-point precision LWD may use different values for the luminance and the color difference, but here, for the sake of simplicity, the fixed-point precision LWD will be described without being explicitly divided for each color signal. For example, when w0C is expressed as a real value, it is 1.0 (1 in binary notation), when LWD is 5, the first weight coefficient is 32 (100,000 in binary notation), and w1C is expressed as a real value. In the case of 2.0 (10 in binary notation) and 5 in LWD, the second weighting coefficient is 64 (1000000 in binary notation). The first offset o0C is an offset corresponding to the first predicted image, and the second offset o1C is an offset corresponding to the second predicted image.

When the WP parameter information is input, the WP parameter control unit 303 checks whether the value of the weight information is within the specified range, resets the value outside the range to the value within the range, or sets the value outside the range to the value within the range. Change the value of the WP application flag. For example, when w0C is expressed as a real value and LWD is 7, the first weighting coefficient is 384. Here, 384 is outside the range of the first weighting coefficient and cannot be used, but 96 is within the range of the first weighting coefficient and can be used. In this case, the WP parameter control unit 303 sets the LWD to 5 and the first weighting factor to 96, so that when w0C is expressed as a real value, the first weighting factor remains within the range of 3.0. It may be set. At this time, the WP parameter control unit 303 may perform the quantization process. For example, when the LWD is 7 and the first weighting factor is 385, the WP parameter control unit 303 performs quantization processing to set the first weighting factor to 384, and then sets the LWD to 5 and w0C to a real value. The first weighting factor may be reset to 96 by setting it to 3.0 when expressed. Further, the WP parameter control unit 303 may change the value of the first WP application flag from 1 to 0 so that the weighted motion compensation prediction is not used. Although not limited to these methods, the WP parameter control unit 303 controls so that the value of the weight information is not used beyond the specified range defined by the specifications and the like.

The WP selectors 304 and 305 switch the connection end of each predicted image based on the WP application flag input from the WP parameter control unit 303. The WP selectors 304 and 305 connect their output ends to the default motion compensation unit 301 when their respective WP application flags are 0. Then, the WP selectors 304 and 305 output the first predicted image and the second predicted image and input them to the default motion compensation unit 301. On the other hand, the WP selectors 304 and 305 connect their output ends to the weighted motion compensation unit 302 when their respective WP application flags are 1. Then, the WP selectors 304 and 305 output the first predicted image and the second predicted image and input them to the weighted motion compensation unit 302.

The default motion compensation unit 301 performs average value processing (default motion compensation prediction) based on the two unidirectional prediction images (first prediction image and second prediction image) input from the WP selectors 304 and 305, and predicts the image. To generate. Specifically, when the first WP application flag and the second WP application flag are 0, the default motion compensation unit 301 performs average value processing based on the mathematical formula (1).

P [x, y] = Clip1 ((PL0 [x, y] + PL1 [x, y] + offset2) >> (shift2)) ... (1)

Here, P [x, y] is a predicted image, PL0 [x, y] is a first predicted image, and PL1 [x, y] is a second predicted image. Offset2 and shift2 are parameters of the rounding process in the average value processing, and are determined by the internal calculation accuracy of the first predicted image and the second predicted image. Clip1 (X) is a function that clips the variable X within the bit precision of the predicted image, and here, it clips the variable X within the bit precision of the predicted image. For example, when the bit precision of the predicted image is L = 8, values outside the range of 0 to 255 are clipped from 0 to 255. More specifically, a value less than or equal to 0 is set to 0, and a value greater than 255 is set to 255.

Assuming that the bit precision of the predicted image is L and the bit precision of the first predicted image and the second predicted image is M (L ≦ M), shift2 is formulated by the mathematical formula (2) and offset2 is formulated by the mathematical formula (3). Will be done.

shift2 = (ML + 1) ... (2)

offset2 = (1 << (shift2-1) ... (3)

For example, when the bit precision of the predicted image is 8 and the bit precision of the first predicted image and the second predicted image is 14, shift2 = 7 from the formula (2) and offset2 = (1 << from the formula (3). 6).

When the prediction mode indicated by the motion information (prediction parameter) is unidirectional prediction, the default motion compensation unit 301 uses only the first prediction image to obtain the final prediction image based on the mathematical formula (4). calculate.

P [x, y] = Clip1 ((PLX [x, y] + office1) >> (shift1)) ... (4)

Here, PLX [x, y] indicates a unidirectional prediction image (first prediction image), and X is an identifier indicating either 0 or 1 in the reference list. For example, when the reference list is 0, it is PL0 [x, y], and when the reference list is 1, it is PL1 [x, y]. Offset1 and shift1 are parameters of the rounding process and are determined by the internal calculation accuracy of the first predicted image. Assuming that the bit precision of the predicted image is L and the bit precision of the first predicted image is M, shift1 is formulated by the mathematical formula (5), and offset1 is formulated by the mathematical formula (6).

shift1 = (ML) ... (5)

offset1 = (1 << (shift1-1) ... (6)

For example, when the bit precision of the predicted image is 8 and the bit precision of the first predicted image is 14, shift1 = 6 from the mathematical formula (5) and offset1 = (1 << 5) from the mathematical formula (6).

The weighted motion compensation unit 302 is based on the two unidirectional prediction images (first prediction image and second prediction image) input from the WP selectors 304 and 305 and the weight information input from the WP parameter control unit 303. Performs weighted motion compensation (weighted motion compensation prediction).

Here, the weighting coefficient will be further described. FIG. 7 is a reference diagram for explaining the weighting coefficient, and shows an example of a change in the gradation value of a moving image in which there is a change in the pixel value in the time direction. In the example shown in FIG. 7, the frame to be encoded is Frame (t), the frame immediately before in time is Frame (t-1), and the frame one frame after in time is Frame (t + 1). As shown in FIG. 7, in a fade image that changes from white to black, the brightness (gradation value) of the image decreases with time. The value of the weighting coefficient means the degree of change in the pixel value as described in FIG. 7, and is a value of 1.0 when expressed as a real value when there is no change in the pixel value (when the change in the pixel value is 0). I take the.

Here, the case where there is no change in the pixel value will be further described. For example, assuming a moving image in which the same still image is continuous in time, the change in brightness between screens is zero. In this case, since the pixel value change is 0 even if the weighted motion compensation unit 302 performs the weighted motion compensation prediction, it is equivalent to performing the default motion compensation prediction. In such a case, that is, when there is no change in the pixel value, the weighted motion compensation unit 302 realizes the default motion compensation prediction by the weighted motion compensation prediction by selecting the reference value of the weighting coefficient. Here, the reference value of the weighting coefficient can be derived according to the fixed-point accuracy, and becomes (1 << LWD).

Further, in general, the pixel value change of the moving image such as the fade effect and the dissolve effect does not change so much for each frame, so the value of the weighting coefficient is biased to around 1.0 when expressed as a real value. .. In the first embodiment, the value of the weighting coefficient is quantized to a fixed-point accuracy indicated by a power of 2, so even if a slight change in the average pixel value between the two images occurs, it is 1 /. If the change is less than 128 precision, the weighting factor value is quantized to 1.0 when expressed in real values. Therefore, in the first embodiment, even if a pixel value change occurs, it can be treated as a case where there is substantially no pixel value change. In the following, for the sake of simplicity, the description will be made on the assumption that there is no change in the pixel value, that is, the value of the weighting coefficient is 1.0 when expressed as a real value. When there is no change in the pixel value, it corresponds to the change in the pixel value being equal to or less than a predetermined value (a value sufficiently smaller than the accuracy of the weighting coefficient).

Therefore, when the first WP application flag and the second WP application flag are 1, the weighted motion compensation unit 302 performs the weighting process based on the mathematical formula (7).

P [x, y] = Clip1 ((((PL0 [x, y] * w0C + PL1 [x, y] * w1C + ((o0C + o1C + 1) << LWD)) >> (LWD + 1))) ... (7)

The weighted motion compensation unit 302 realizes the rounding process by controlling the LWD as in the mathematical formula (8) when the calculation accuracy of the first predicted image and the second predicted image is different from that of the predicted image.

LWD'= LWD + offset1 ... (8)

The rounding process can be realized by replacing the LWD of the mathematical formula (7) with the LWD'of the mathematical formula (8). For example, when the bit accuracy of the predicted image is 8 and the bit accuracy of the first predicted image and the second predicted image is 14, by resetting the LWD, the calculation accuracy is the same as that of shift2 of the equation (1). It is possible to realize batch rounding processing.

When the prediction mode indicated by the motion information (prediction parameter) is unidirectional prediction, the weighted motion compensation unit 302 uses only the first prediction image and the final prediction image based on the mathematical formula (9). Is calculated.

P [x, y] = Clip1 ((PLX [x, y] * wXC + (1 << (LWD-1))) >> (LWD) + oXC) ... (9)

Here, PLX [x, y] indicates a unidirectional prediction image (first prediction image), wXC indicates a weighting coefficient corresponding to unidirectional prediction, and X indicates either 0 or 1 in the reference list. It is an identifier to indicate, and oXC indicates an offset corresponding to unidirectional prediction. For example, when the reference list is 0, it is PL0 [x, y], w0C, o0C, and when the reference list is 1, it is PL1 [x, y], w1C, o1C.

When the calculation accuracy of the first prediction image and the second prediction image is different from that of the prediction image, the weighted motion compensation unit 302 controls the LWD as in the mathematical formula (8) as in the case of the bidirectional prediction. Achieve rounding processing.

The rounding process can be realized by replacing the LWD of the mathematical formula (9) with the LWD'of the mathematical formula (8). For example, when the bit precision of the predicted image is 8 and the bit precision of the first predicted image is 14, by resetting the LWD, a batch rounding process with the same calculation precision as shift 1 of the mathematical formula (4) is realized. It becomes possible to do.

In the case of unidirectional prediction, various parameters (second WP adaptation flag, second weighting coefficient, and second offset information) corresponding to the second prediction image are not used, so they are set to predetermined initial values. It may have been done.

Returning to FIG. 1, the motion evaluation unit 109 evaluates motion between a plurality of frames based on the input image and the reference image input from the prediction image generation unit 107, outputs motion information and WP parameter information, and outputs motion information. It is input to the prediction image generation unit 107 and the coding unit 110, and the WP parameter information is input to the prediction image generation unit 107 and the index setting unit 108.

The motion evaluation unit 109 calculates an error by calculating a difference value starting from a plurality of reference images corresponding to the same position as the input image of the prediction target pixel block, shifts this position with fractional accuracy, and minimizes the error. Optimal motion information is calculated by a method such as block matching. In the case of bidirectional prediction, the motion evaluation unit 109 uses the motion information derived by the unidirectional prediction to perform block matching including the default motion compensation prediction as shown in the mathematical formulas (1) and (4). By doing so, the motion information of the two-way prediction is calculated.

At this time, the motion evaluation unit 109 can calculate the WP parameter information by performing block matching including the weighted motion compensation prediction as shown by the mathematical formulas (7) and (9). In addition, in the calculation of the WP parameter information, a method of calculating the weighting coefficient and the offset using the pixel gradient of the input image, a method of calculating the weighting coefficient and the offset by accumulating the prediction error at the time of encoding, and the like may be used. Good. Further, as the WP parameter information, a fixed value predetermined for each coding device may be used.

Here, with reference to FIG. 7 again, a method of calculating the weighting coefficient, the fixed-point accuracy of the weighting coefficient, and the offset from the moving image in which the pixel value changes with time will be described. As described above, in the fade image that changes from white to black as shown in FIG. 7, the pixel value (gradation value) decreases with time. The motion evaluation unit 109 can calculate the weighting coefficient by calculating this slope.

Further, the fixed-point accuracy of the weighting coefficient is information indicating the accuracy of this inclination, and the motion evaluation unit 109 can calculate an optimum value from the temporal distance of the reference image and the degree of change of the image value. For example, in FIG. 7, if the value of the weighting coefficient between Frame (t-1) and Frame (t + 1) is 0.75 when expressed with real number precision, 3/4 can be expressed with 1/4 precision. Therefore, the motion evaluation unit 109 sets the fixed-point precision to 2 (1 << 2). Since the fixed-point precision value affects the code amount when the weighting coefficient is encoded, the optimum value may be selected in consideration of the code amount and the prediction accuracy. The fixed-point precision value may be a predetermined fixed value.

Further, when the slopes do not match, the motion evaluation unit 109 can calculate the offset value by obtaining the correction value (deviation amount) corresponding to the intercept of the linear function. For example, in FIG. 7, when the value of the weighting coefficient between Frame (t-1) and Frame (t + 1) is expressed by real number precision, it is 0.60, and when the fixed point precision is 1 (1 << 1), it is There is a high possibility that the weighting coefficient is set to 1 (that is, it corresponds to 0.50 when the value of the weighting coefficient is expressed by real number precision). In this case, since the decimal point precision of the weighting coefficient deviates from the optimum value of 0.60 by 0.10, the motion evaluation unit 109 calculates the correction value for this amount from the maximum value of the pixel and uses it as an offset value. Set. When the maximum value of the pixel is 255, the motion evaluation unit 109 may set a value such as 25 (255 × 0.1).

In the first embodiment, the motion evaluation unit 109 is illustrated as one function of the coding device 100, but the motion evaluation unit 109 is not an essential configuration of the coding device 100, and for example, the motion evaluation unit 109 is coded. It may be a device outside the conversion device 100. In this case, the motion information and the WP parameter information calculated by the motion evaluation unit 109 may be loaded into the coding device 100.

The index setting unit 108 receives the WP parameter information input from the motion evaluation unit 109, confirms the reference list (list number) and the reference image (reference number), outputs the index information, and outputs the index information to the coding unit 110. input. The index setting unit 108 maps the WP parameter information input from the motion evaluation unit 109 to a syntax element described later to generate index information. At this time, the index setting unit 108 derives a selection range of the weighting coefficient and confirms that the weighting coefficient is included in the selection range.

Here, the derivation of the selection range of the weighting coefficient will be described.

In the first embodiment, as described above, it is assumed that there is no change in the pixel value and the weight coefficient value is expressed as a real value of 1.0. In this case, the weight coefficient / weight coefficient reference value is assumed. = 1 holds. Since the reference value of the weighting coefficient is (1 << LWD) as described above, in the first embodiment, the weighting coefficient is (1 << LWD), which is the same value as the reference value of the weighting coefficient.

By the way, H. In 264 and the like, indexes such as weighting factors and offsets are specified to take a signed 8-bit value from -128 to 127, and fixed-point precision is specified to take a value from 0 to 7. .. Therefore, in the first embodiment, the weighting coefficient may be out of the specified range.

FIG. 8 shows H. It is a reference figure which shows the selection range of the weighting coefficient in 264, and shows the weighting coefficient (1 << LWD) when the fixed-point precision LWD takes a value of 0 to 7, respectively. As is clear from FIG. 8, the weighting coefficient takes a positive value near 0 when the value of the fixed-point precision LWD becomes small, but becomes 128 when the value of the fixed-point precision LWD becomes 7, and H. It is out of the range specified in 264.

Thus, H. According to the regulation of 264, the range of the weighting coefficient to be used is out of the specified range, which may not be in accordance with the practical aspect. Further, in the unidirectional prediction, even if the weighting coefficient corresponding to the negative direction is selected, the predicted pixel value output by the unidirectional prediction is likely to be clipped to the bit range of the input image and become 0, which is negative. The weighting factor corresponding to the direction of is virtually unselectable. On the other hand, in bidirectional prediction, in order to realize extrapolation prediction, it is possible to set the weighting factor of one unidirectional prediction to a negative value and the weighting factor of the other to a positive value. In many cases, the value on the negative side does not require the same accuracy as the value on the positive side as the range of the weighting coefficient.

Therefore, in the first embodiment, the index setting unit 108 derives a selection range of the weighting coefficient by allocating values in the negative direction and the positive direction with the reference value of the weighting coefficient as a substantially center, and the derived weighting coefficient Make sure that the weighting factor is within the selection of.

FIG. 9 is an explanatory diagram showing an example of the selection range of the weighting coefficient of the first embodiment. In the example shown in FIG. 9, unlike the weighting coefficient selection range described with reference to FIG. 8, the weighting coefficient reference value (1 << LWD) is arranged so as to be located substantially at the center of the selection range, and the weighting factor reference is provided. The value obtained by subtracting 128 from the value (-128 + (1 << LWD)) is the minimum value of the selection range, and the value obtained by adding 127 to the reference value of the weighting coefficient (127+ (1 << LWD)) is the maximum value of the selection range. It is a value.

The index setting unit 108 sets the selection range of the weighting coefficient by using the mathematical formula (10) and the mathematical formula (11). The formula (10) formulates the minimum value of the selection range, and the formula (11) formulates the maximum value of the selection range.

min_wXC = -128 + (1 << LWD) ... (10)

max_wXC = 127+ (1 << LWD) ... (11)

10A and 10B are explanatory views showing a specific example of the selection range of the weighting coefficient of the first embodiment, and FIG. 10A shows the selection range of the weighting coefficient when the value of the fixed-point precision LWD is 7. FIG. 10B shows a selection range of weighting factors when the value of the fixed-point precision LWD is 5. In the example shown in FIG. 10A, 128, which is a reference value of the weighting coefficient, is arranged so as to be located substantially in the center of the selection range, the minimum value of the selection range is 0, and the maximum value of the selection range is 255. In the example shown in FIG. 10B, 32, which is a reference value of the weighting coefficient, is arranged so as to be located substantially in the center of the selection range, the minimum value of the selection range is -96, and the maximum value of the selection range is 159. ..

FIG. 11 shows H. It is a reference figure which shows the minimum value and the maximum value of the selection range of a weighting coefficient in 264, and FIG. 12 is an explanatory diagram which shows an example of the minimum value and the maximum value of the selection range of a weighting coefficient of 1st Embodiment. As shown in FIG. 11, H. In 264, the minimum value and the maximum value of the selection range of the weighting coefficient do not depend on the reference value of the weighting coefficient and are constant. On the other hand, as shown in FIG. 12, in the first embodiment, the minimum value and the maximum value of the selection range of the weighting coefficient vary depending on the reference value of the weighting coefficient.

As shown in FIG. 12, when the selection range of the weighting factor is set with the reference value of the weighting factor as the substantially center, the range that the weighting factor can take is -127 to 255, and a signed 9-bit accuracy is required. .. Therefore, in the first embodiment, the coding unit 110 described later updates the weighting coefficient set as an index, that is, the value to be coded, to the difference value between the weighting coefficient and the reference value of the weighting coefficient. As shown in FIG. 9, when the reference value of the weighting coefficient is subtracted from the selected range of the derived weighting coefficient, it can be seen that the range of the difference value of the weighting coefficient takes a signed 8-bit value from −128 to 127. In other words, when the weighting factor selection range is set with the weighting factor reference value as the approximate center, the weighting factor selection range varies depending on the weighting factor reference value, but the weighting factor selection range is used as the weighting factor reference value. By subtracting the values, the range of the difference value of the weighting coefficient becomes constant without depending on the reference value of the weighting coefficient. As described above, in the first embodiment, since the weighting coefficient is replaced with the difference value of the weighting coefficient, the selection range of the weighting coefficient can be expanded and the selection range of the signed 8-bit precision can be defined.

When the index setting unit 108 confirms that the weighting coefficient is not included in the derived weighting coefficient selection range, the index setting unit 108 may perform clipping processing using the maximum value or the minimum value of the weighting coefficient selection range. Good. In this case, the index setting unit 108 may clip at the minimum value if the weighting coefficient is smaller than the minimum value of the selection range, and clip at the maximum value if the weighting coefficient is larger than the maximum value of the selection range. By introducing such a clip process, the value to be encoded such as the difference value of the weighting coefficient takes a value within a predetermined bit accuracy without setting a specific range constraint, so that the hardware Can clarify the configuration of the circuit scale used by.

Further, in the first embodiment, it is assumed that the selection range of the weighting coefficient has a precision of signed 8-bit, but the precision of the selection range of the weighting coefficient is not limited to this, and is, for example, signed. The accuracy may be 9 bits. In this case, the selection range of the weighting coefficient is from -256 to 255, but -128 of the mathematical formula (10) may be replaced with -256, and 127 of the mathematical formula (11) may be replaced with 255.

Further, in the first embodiment, an example in which the index setting unit 108 derives the selection range of the weighting coefficient has been described, but the present invention is not limited to this, and the coding unit 110 may perform the derivation. That is, the index setting unit 108 may be used as a derivation unit, or the coding unit 110 may be used as a derivation unit.

13A and 13B are diagrams showing an example of WP parameter information input to the index setting unit 108 of the first embodiment. An example of WP parameter information at the time of P-slice is as shown in FIG. 13A, and an example of WP parameter information at the time of B-slice is as shown in FIGS. 13A and 13B. The list number is an identifier indicating the prediction direction, and takes a value of 0 at the time of unidirectional prediction, and takes two values of 0 and 1 at the time of bidirectional prediction because two types of prediction can be used. The reference number is a value corresponding to 1 to N shown in the frame memory 206. Since the WP parameter information is held for each reference list and reference image, the information required at the time of B-slice is 2N, assuming that there are N reference images.

FIG. 14 is a flowchart showing an example of the derivation process of the selection range of the weighting coefficient of the first embodiment. Here, the description will be made on the assumption that the index setting unit 108 performs the derivation process of the selection range of the weighting coefficient, but as described above, the coding unit 110 may perform the process.

First, the index setting unit 108 derives the fixed-point precision LWD of the weighting coefficient (step S02). Here, the index setting unit 108 may derive the fixed-point precision LWD of the weighting coefficient from the WP parameter information or may derive it from the index information.

Subsequently, the index setting unit 108 derives a reference value (1 << LWD) of the weighting coefficient by using the derived fixed-point precision LWD (step S03).

Subsequently, the index setting unit 108 subtracts 128 from the derived weight coefficient reference value (1 << LWD) to derive the minimum value of the weight coefficient selection range (step S04).

Subsequently, the index setting unit 108 adds 127 to the derived reference value (1 << LWD) of the weighting coefficient, and derives the maximum value of the selection range of the weighting coefficient (step S05).

Then, the index setting unit 108 confirms that the weighting coefficient is included in the selected range of the derived weighting coefficient.

Returning to FIG. 1, the coding unit 110 selects the quantization conversion coefficient input from the quantization unit 103, the motion information input from the motion evaluation unit 109, the index information input from the index setting unit 108, and the weighting coefficient. Encoding processing is performed on various coding parameters such as the range and the quantization information specified by the coding control unit 111, and the coding data is generated. The coding process corresponds to, for example, Huffman coding or arithmetic coding.

The coding parameter is a parameter required for decoding such as prediction information indicating a prediction method, information on a quantization conversion coefficient, and information on quantization. For example, the coding control unit 111 has an internal memory (not shown), the coding parameters are held in the internal memory, and when coding the pixel blocks, the coding parameters of the adjacent already coded pixel blocks are used. Can be done. For example, H. In the intra-prediction of 264, the prediction information of the pixel block can be derived from the prediction information of the encoded adjacent block.

The coding unit 110 outputs the generated coded data according to an appropriate output timing managed by the coded control unit 111. In the output coded data, for example, various information is multiplexed by a multiplexing unit (not shown) and temporarily stored in an output buffer (not shown), and then, for example, a storage system (not shown) ( It is output to the storage media) or the transmission system (communication line).

The coding unit 110 includes an entropy coding unit 110A and an index reconstruction unit 110B.

The entropy coding unit 110A performs coding processing such as variable length coding and arithmetic coding on the input information. For example, H. In 264, context-adaptive variable-length coding (CAVLC) and context-adaptive arithmetic coding (CABAC: Context-based Adaptive Binary Coding) are used.

In order to reduce the code length of the syntax element of the index information input from the index setting unit 108, the index reconstruction unit 110B performs prediction processing according to the characteristics of the parameters of the syntax element, and the value of the syntax element as it is (direct). The value) and the difference value of the predicted value are calculated and output to the entropy encoding unit 110A. A specific example of the prediction process will be described later. When the coding unit 110 derives the selection range of the weighting coefficient, the index reconstruction unit 110B will perform the derivation.

FIG. 15 is a diagram showing an example of the syntax 500 used by the coding device 100 of the first embodiment. The syntax 500 shows the structure of the coded data generated by the coding device 100 encoding the input image (moving image data). When decoding the coded data, the decoding device described later performs the syntax interpretation of the moving image data with reference to the same syntax structure as the syntax 500.

The syntax 500 includes three parts: high-level syntax 501, slice-level syntax 502, and coding tree-level syntax 503. The high level syntax 501 contains the syntax information of the layer above the slice. The syntax information includes, for example, the tile-shaped division information described in the example shown in FIG. 2B. Slice refers to a rectangular or continuous area contained in a frame or field. The slice level syntax 502 contains the information required to decode each slice. The coding tree level syntax 503 contains the information necessary to decrypt each coding tree (ie, each coding tree block). Each of these parts contains more detailed syntax.

High-level syntax 501 includes sequence and picture-level syntax such as sequence parameter set syntax 504, picture parameter set syntax 505, and adaptation parameter set syntax 506.

The slice level syntax 502 includes a slice header syntax 507, a pred weight table syntax 508, a slice data syntax 509, and the like. The pred weight table syntax 508 is called from the slice header syntax 507.

The coding tree level syntax 503 includes a coding tree unit syntax 510, a transform unit syntax 511, a prediction unit syntax 512, and the like. The coding tree unit Syntax 510 can have a quadtree structure. Specifically, the coding tree unit syntax 510 can be recursively called as a syntax element of the coding tree unit syntax 510. That is, one coding tree block can be subdivided into quadtrees. Further, the transform unit syntax 511 is included in the coding tree unit syntax 510. The transform unit syntax 511 is called in each coding tree unit syntax 510 at the end of the quadtree. The transform unit syntax 511 describes information related to inverse orthogonal transformation, quantization, and the like. Information about weighted motion compensation predictions may be described in these syntaxes.

FIG. 16 is a diagram showing an example of the picture parameter set syntax 505 of the first embodiment. The weighted_pred_flag is, for example, a syntax element indicating the validity or invalidity of the weighted compensation prediction of the first embodiment regarding P-slice. When weighted_pred_flag is 0, the weighted motion compensation prediction of the first embodiment in P-slice becomes invalid. Therefore, the WP application flag included in the WP parameter information is always set to 0, and the WP selectors 304 and 305 connect their respective output ends to the default motion compensation unit 301. On the other hand, when weighted_pred_flag is 1, the weighted motion compensation prediction of the first embodiment in P-slice is valid.

As another example, when weighted_pred_flag is 1, in the syntax of lower layers (slice header, coding tree block, transform unit, prediction unit, etc.), the first is for each local area inside the slice. One embodiment may specify the validity or invalidity of the weighted motion compensation prediction.

The weighted_bipred_idc is, for example, a syntax element indicating the validity or invalidity of the weighted compensation prediction of the first embodiment regarding B-slice. When weighted_bipred_idc is 0, the weighted motion compensation prediction of the first embodiment in B-slice becomes invalid. Therefore, the WP application flag included in the WP parameter information is always set to 0, and the WP selectors 304 and 305 connect their respective output ends to the default motion compensation unit 301. On the other hand, when weighted_bipred_idc is 1, the weighted motion compensation prediction of the first embodiment in B-slice is valid.

As another example, when weighted_bipred_idc is 1, in the syntax of lower layers (slice header, coding tree block, transform unit, etc.), for each local region inside the slice, the first embodiment The validity or invalidity of the weighted motion compensation prediction may be specified.

FIG. 17 is a diagram showing an example of the slice header syntax 507 of the first embodiment. slice_type indicates the slice type of the slice (I-slice, P-slice, B-slice, etc.). The pic_parameter_set_id is an identifier indicating which picture parameter set syntax 505 is to be referred to. num_ref_idx_active_override_flag is a flag indicating whether to update the number of valid reference images. When this flag is 1, num_ref_idx_l0_active_minus1 and num_ref_idx_l1_active_minus1 that define the number of reference images in the reference list can be used. pred_weight_table () is a function indicating the pred weight table syntax used for weighted motion compensation prediction, and this function is used when the weighted_pred_flag is 1 and P-slice, and when weighted_bipred_idc is 1 and B-slice. Called.

FIG. 18 is a diagram showing an example of the pred weight table syntax 508 of the first embodiment. luma_log2_weight_denom represents the fixed-point precision (LWD) of the weighting coefficient of the luminance signal in the slice, and is a value corresponding to the LWD of the formula (7) or the formula (9). delta_chroma_log2_weight_denom represents the fixed-point accuracy of the weighting factor of the color difference signal in the slice, and the derivation method will be described later. chroma_format_idc is an identifier representing a color space, and MONO_IDX is a value indicating a monochrome image. num_ref_common_active_minus1 indicates the value obtained by subtracting 1 from the number of reference images included in the common list in the slice.

luma_weight_l0_flag and luma_weight_l1_flag indicate the WP adaptation flags in the luminance signals corresponding to List 0 and List 1, respectively. When this flag is 1, the weighted motion compensation prediction of the luminance signal of the first embodiment is effective in the entire area within the slice. chroma_weight_l0_flag and chroma_weight_l1_flag indicate the WP adaptation flags in the color difference signals corresponding to List 0 and List 1, respectively. When this flag is 1, the weighted motion compensation prediction of the color difference signal of the first embodiment is effective in the entire area within the slice. luma_weight_l0 [i] and luma_weight_l1 [i] are the weighting coefficients of the luminance signals corresponding to the i-th reference number managed in List 0 and List 1, respectively. luma_offset_l0 [i] and luma_offset_l1 [i] are the offsets of the luminance signals corresponding to the i-th reference number managed in List 0 and List 1, respectively. These are the values corresponding to w0C, w1C, o0C, and o1C of the mathematical formula (7) or the mathematical formula (9), respectively. However, C = Y.

chroma_weight_l0 [i] [j] and chroma_weight_l1 [i] [j] are the weight coefficients of the color difference signals corresponding to the i-th reference number managed in List 0 and List 1, respectively. chroma_offset_l0 [i] [j] and chroma_offset_l1 [i] [j] are the offsets of the color difference signals corresponding to the i-th reference number managed in List 0 and List 1, respectively. These are the values corresponding to w0C, w1C, o0C, and o1C of the mathematical formula (7) or the mathematical formula (9), respectively. However, C = Cr or Cb. j indicates a component of a color difference component. For example, in the case of a YUV4: 2: 0 signal, j = 0 is a Cr component and j = 1 is a Cb component. In this notation, j = 0 may be used as the Cb component and j = 1 may be used as the Cr component.

Here, the details of the prediction method of each syntax element related to the weighted prediction in the syntax configuration will be described. The prediction of the syntax element is performed by the index reconstruction unit 110B. In the example shown in FIG. 18, the syntax elements into which the predictions are introduced are prefixed with delta.

First, a method of predicting between the signals of luma_log2_weight_denom and chroma_log2_weight_denom, which indicate the fixed-point accuracy of the weighting coefficient, will be described. The index reconstruction unit 110B uses the mathematical formula (12) to perform prediction processing between the signals of luma_log2_weight_denom and chroma_log2_weight_denom, and uses the mathematical formula (13) to perform restoration processing. Here, as shown in FIG. 18, since luma_log2_weight_denom is defined first, chroma_log2_weight_denom is predicted from the value of luma_log2_weight_denom.

delta_chroma_log2_weight_denom = (chroma_log2_weight_denom --luma_log2_weight_denom)… (12)

chroma_log2_weight_denom = (luma_log2_weight_denom + delta_chroma_log2_weight_denom)… (13)

Since the fade effect generally causes different temporal changes depending on the color space, the fixed-point accuracy for each signal component has a strong correlation between the luminance component and the color difference component. Therefore, by making predictions in the color space in this way, the amount of information indicating fixed-point accuracy can be reduced.

Although the luminance component is subtracted from the color difference component in the mathematical formula (12), the luminance component may be subtracted from the luminance component. In this case, the formula (13) may be modified according to the formula (12).

Next, a method for predicting luma_weight_lx [i] and chroma_weight_lx [i] [j], which represent the weight coefficients of the luminance and color difference signals, respectively, will be described. Here, x is an identifier indicating 0 or 1. The values of luma_weight_lx [i] and chroma_weight_lx [i] [j] change according to the values of luma_log2_weight_denom and chroma_log2_weight_denom, respectively. For example, when the value of luma_log2_weight_denom is 3, luma_weight_lx [i] when there is no pixel value change is (1 << 3). On the other hand, when the value of luma_log2_weight_denom is 5, luma_weight_lx [i] is (1 << 5) assuming that there is no change in brightness.

Therefore, the index reconstruction unit 110B performs prediction processing using the weighting coefficient (default value) when there is no change in the pixel value. Specifically, the index reconstruction unit 110B performs the prediction process of luma_weight_lx [i] using the mathematical formulas (14) to (15), and performs the restoration process using the mathematical formula (16). Similarly, the index reconstruction unit 110B performs the prediction process of chroma_weight_lx [i] using the mathematical formulas (17) to (18), and performs the restoration process using the mathematical formula (19).

delta_luma_weight_lx [i] = (luma_weight_lx [i] --default_luma_weight_lx)… (14)

default_luma_weight_lx = (1 << luma_log2_weight_denom)… (15)

luma_weight_lx [i] = (default_luma_weight_lx + delta_luma_weight_lx [i])… (16)

delta_chroma_weight_lx [i] [j] = (chroma_weight_lx [i] [j] --default_chroma_weight_lx)… (17)

default_chroma_weight_lx = (1 << chroma_log2_weight_denom)… (18)

chroma_weight_lx [i] [j] = (default_chroma_weight_lx + delta_chroma_weight_lx [i] [j])… (19)

Here, default_luma_weight_lx and default_chroma_weight_lx are reference values (default values) in which there is no change in pixel values in the luminance component and the color difference component, respectively.

An image containing a fade effect fades at a specific fade change point, and other images are often normal natural images or images without a fade effect. In this case, the weighting coefficient is often taken when there is no change in the pixel value. Therefore, the sign amount of the weighting coefficient can be reduced by deriving the initial value when there is no change in the pixel value from the fixed-point accuracy and using it as the predicted value.

Next, a method for predicting chroma_offset_lx [i] [j], which represents the offset of the color difference signal, will be described. In the YUV color space, the color difference component expresses a color by the amount of deviation from the median value. Therefore, the amount of change from the pixel value change in consideration of the median value can be used as the predicted value by using the weighting coefficient. Specifically, the index reconstruction unit 110B performs prediction processing of chroma_offset_lx [i] [j] using mathematical formulas (20) to (21), and restores processing using mathematical formulas (22).

delta_chroma_offset_lx [i] [j] = (chroma_offset_lx [i] [j] + ((MED * chroma_weight_lx [i] [j]) >> chroma_log2_weight_denom) --MED)… (20)

MED = (MaxChromaValue >> 1)… (21)

Here, MaxChromaValue indicates the maximum pixel value at which a color difference signal can be obtained. For example, for an 8-bit signal, MaxChromaValue is 255 and MED is 128.

chroma_offset_lx [i] [j] = (delta_chroma_offset_lx [i] [j]-((MED * chroma_weight_lx [i] [j]) >> chroma_log2_weight_denom) + MED)… (22)

By using the signal characteristics of the color difference signal and introducing a predicted value that takes into account the amount of deviation from the median, the code amount of the offset value of the color difference signal is reduced compared to the case where the offset value is encoded as it is. it can.

FIG. 19 is an explanatory diagram showing an example of the relationship between the values of the syntax elements of the first embodiment, and shows the relationship between the values of luma_log2_weight_denom, default_luma_weight_lx, luma_weight_lx [i], and delta_luma_weight_lx [i]. As shown in FIG. 19, the delta_luma_weight_lx [i], which is a syntax element encoded by the entropy coding unit 110A, that is, the range in which the difference value of the weighting coefficient can be taken is fixed in the range of −128 to 127. , Signed 8-bit accuracy.

As described above, in the first embodiment, the selection range of the weighting coefficient is derived and derived by allocating the values in the negative direction and the positive direction with the reference point of the weighting coefficient at which the pixel value change is 0 as substantially the center. Make sure that the weighting factor is within the selection range of the weighting factor. Therefore, according to the first embodiment, H. Compared with 264 and the like, the selection range of the weighting coefficient can be expanded, and it is possible to easily take the value on the positive side with high selection frequency. Further, according to the first embodiment, since the difference value of the weighting coefficient to be coded takes a signed 8-bit value from −128 to 127 as a fixed value, it is signed while expanding the selection range of the weighting coefficient. A selection range with 8-bit accuracy can be specified.

As described above, in the first embodiment, since the range of the encoding syntax (difference value of the weighting coefficient) can be fixed, the specification is compared with the configuration in which the encoder dynamically changes these ranges. Can be simplified. For example, when the syntax to be encoded is used as the weighting coefficient and the selection range of the weighting coefficient fluctuates according to the reference value of the weighting coefficient, the reference value of the weighting coefficient is associated with the minimum and maximum values of the selection range of the weighting coefficient. It is necessary to prepare a table and refer to it each time after deriving the selection range of the weighting factor, or to calculate and derive the selection range of the weighting coefficient each time. In such a case, a configuration in which the table is loaded into the memory and referenced each time, or an arithmetic circuit for calculating the selection range of the weighting coefficient each time is required, which increases the hardware scale. On the other hand, in the first embodiment, since the range of the encoding syntax (difference value of the weighting coefficient) can be fixed, the hardware scale is reduced without being restricted by the hardware configuration as described above. be able to.

Further, in the first embodiment, the difference value of the weighting coefficient whose range is fixed to the signed 8-bit accuracy is encoded, but the difference value of the weighting coefficient takes a value near the center of the range (near 0). Therefore, the code length at the time of coding can be shortened, and the coding efficiency can be improved. H. In 264 and the like, the weighting coefficient is encoded by a signed exponential Golomb code (se (v)), which is a valid code for a symbol whose encoded value increases exponentially with respect to 0. Therefore, it is common to set the most frequently used reference value as the center of the range. In the first embodiment, the case where the pixel value change between pictures is 0 in a general moving image is set as the reference value of the weighting coefficient, and the prediction from the above-mentioned reference value is also introduced in the prediction of the selection range of the weighting coefficient. ing. As a result, the exponential Golomb code matches the selection range of the prediction and weighting coefficients, so the code amount reduction effect is high, and the coefficient range is determined around the reference value, so even if a large value is taken, it will be a positive value. The distance from the reference value of the negative value becomes about the same, and it has the effect of being able to encode with a shorter code length than the conventional method.

Note that a syntax element not specified in the present embodiment may be inserted between the rows of the syntax table illustrated in FIGS. 16 to 18 of the first embodiment, and other descriptions regarding conditional branching are included. You may. Further, the syntax table may be divided into a plurality of tables, or a plurality of syntax tables may be integrated. In addition, the terms of each of the illustrated syntactic elements can be changed arbitrarily.

(Second Embodiment)
In the second embodiment, a decoding device that decodes the coded data encoded by the coding device of the first embodiment will be described. In the second embodiment as well, as in the first embodiment, the description will be made on the assumption that there is no change in the pixel value, that is, the value of the weighting coefficient is 1.0 when expressed as a real value.

FIG. 20 is a block diagram showing an example of the configuration of the decoding device 800 of the second embodiment.

The decoding device 800 decodes the coded data stored in an input buffer (not shown) or the like into a decoded image, and outputs the encoded data as an output image to an output buffer (not shown). The coded data is output from, for example, the coding device 100 of FIG. 1, and is input to the decoding device 800 via a storage system, a transmission system, a buffer, or the like (not shown).

As shown in FIG. 20, the decoding device 800 includes a decoding unit 801, an inverse quantization unit 802, an inverse orthogonal transform unit 803, an addition unit 804, a prediction image generation unit 805, and an index setting unit 806. Be prepared. The inverse quantization unit 802, the inverse orthogonal transform unit 803, the addition unit 804, and the prediction image generation unit 805 are the inverse quantization unit 104, the inverse orthogonal conversion unit 105, the addition unit 106, and the prediction image generation unit 107, respectively, of FIG. It is an element that is substantially the same as or similar to. The decoding control unit 807 shown in FIG. 20 controls the decoding device 800, and can be realized by, for example, a CPU or the like.

The decoding unit 801 performs decoding based on the syntax for each frame or field for decoding the coded data. The decoding unit 801 includes an entropy decoding unit 801A and an index reconstruction unit 801B.

The entropy decoding unit 801A sequentially entropy-decodes the code string of each syntax, and motion information including a prediction mode, a motion vector, and a reference number, index information for weighted motion compensation prediction, a quantization conversion coefficient, and the like. Reproduce the coding parameters of the coded block. The entropy decoding is also referred to as parsing processing or the like. Here, the coding parameters are all parameters required for decoding, such as information on conversion coefficients and information on quantization, in addition to the above.

Specifically, the entropy decoding unit 801A has a function of performing decoding processing such as variable length decoding processing and arithmetic decoding processing on the input coded data. For example, H. In 264, context-adaptive variable-length coding (CAVLC: Context based Adaptive Variable Length Coding) and context-adaptive arithmetic coding (CABAC: Context-based Adaptive Binary Coding) are used. Is decoded into a meaningful syntax element. These processes are also called decoding processes.

The index reconstruction unit 801B restores the decrypted index information and reconstructs the index information. Specifically, the index reconstruction unit 801B performs prediction processing according to the characteristics of the parameters of the syntax element in order to reduce the code length of the syntax element of the decoded index information, restores the syntax element, and indexes. Reconstruct the information. A specific example of the prediction process will be described later.

The decoding unit 801 outputs motion information, index information, and quantization conversion coefficient, inputs the quantization conversion coefficient to the inverse quantization unit 802, inputs index information to the index setting unit 806, and predicts motion information. Input to the generation unit 805.

The inverse quantization unit 802 performs an inverse quantization process on the quantization conversion coefficient input from the decoding unit 801 to obtain a restoration conversion coefficient. Specifically, the inverse quantization unit 802 performs inverse quantization according to the quantization information used in the decoding unit 801. More specifically, the inverse quantization unit 802 multiplies the quantization step size derived from the quantization information by the quantization conversion coefficient to obtain the restoration conversion coefficient. The inverse quantization unit 802 outputs the restoration conversion coefficient and inputs it to the inverse orthogonal transformation unit 803.

The inverse orthogonal transform unit 803 performs an inverse orthogonal transform corresponding to the orthogonal transform performed on the coding side with respect to the restore conversion coefficient input from the inverse quantization unit 802, and obtains a restore prediction error. The inverse orthogonal transform unit 803 outputs the restoration prediction error and inputs it to the addition unit 804.

The addition unit 804 adds the restoration prediction error input from the inverse orthogonal transform unit 803 and the corresponding predicted image to generate a decoded image. The addition unit 804 outputs the decoded image and inputs it to the prediction image generation unit 805. Further, the addition unit 804 outputs the decoded image as an output image to the outside. The output image is then temporarily stored in an external output buffer or the like (not shown), and is transferred to a display device system such as a display or monitor (not shown) or a video device system according to the output timing managed by the decoding control unit 807, for example. It is output.

The index setting unit 806 receives the index information input from the decoding unit 801, converts it into WP parameter information, outputs it, and inputs it to the prediction image generation unit 805. Specifically, the index setting unit 806 receives the index information that has been decoded by the entropy decoding unit 801A and reconstructed by the index reconstruction unit 801B. Then, the index setting unit 806 confirms the list of reference images and the reference number, converts them into WP parameter information, and outputs the converted WP parameter information to the prediction image generation unit 805. When converting the index information into the WP parameter information, the index setting unit 806 derives a selection range of the weighting coefficient and confirms that the weighting coefficient is included in the selection range. Since the derivation of the selection range of the weighting coefficient is the same as that of the first embodiment, detailed description thereof will be omitted. Further, the derivation of the selection range of the weighting coefficient may be performed not by the index setting unit 806 but by the index reconstruction unit 801B. That is, the index setting unit 806 may be used as a derivation unit, or the index reconstruction unit 801B (decoding unit 801) may be used as a derivation unit.

Further, the WP parameter information includes information on the first WP application flag, the second WP adaptation flag, and the weight information as in the first embodiment. Further, as in the first embodiment, the weight information includes the value w0C of the first weighting coefficient, the value w1C of the second weighting coefficient, the fixed-point accuracy LWD of the first weighting coefficient and the second weighting coefficient, the first offset o0C, and the first Includes information on the two offsets o1C.

The prediction image generation unit 805 generates a prediction image using the motion information input from the decoding unit 801, the WP parameter information input from the index setting unit 806, and the decoded image input from the addition unit 804.

Here, the details of the prediction image generation unit 805 will be described with reference to FIG. Like the prediction image generation unit 107, the prediction image generation unit 805 includes a plurality of frame motion compensation units 201, a memory 202, a unidirectional motion compensation unit 203, a prediction parameter control unit 204, a reference image selector 205, and a frame memory 206. And a reference image control unit 207.

The frame memory 206 stores the decoded image input from the addition unit 106 as the reference image under the control of the reference image control unit 207. The frame memory 206 has a plurality of memory sets FM1 to FMN (N ≧ 1) for temporarily holding the reference image.

The prediction parameter control unit 204 prepares a plurality of combinations of the reference image number and the prediction parameter as a table based on the motion information input from the decoding unit 801. Here, the motion information refers to a motion vector indicating the amount of motion deviation used in motion compensation prediction, a reference image number, information on a prediction mode such as unidirectional / bidirectional prediction, and the like. Prediction parameters refer to information about motion vectors and prediction modes. Then, the prediction parameter control unit 204 selects and outputs a combination of the reference image number and the prediction parameter used for generating the prediction image based on the motion information, inputs the reference image number to the reference image selector 205, and inputs the prediction parameter. Is input to the unidirectional motion compensation unit 203.

The reference image selector 205 is a switch that switches which output terminal of the frame memories FM1 to FMN of the frame memory 206 is connected according to the reference image number input from the prediction parameter control unit 204. For example, if the reference image number is 0, the reference image selector 205 connects the output end of the FM1 to the output end of the reference image selector 205, and if the reference image number is N-1, the reference image selector 205 refers to the output end of the FMN. Connect to the output end of the image selector 205. The reference image selector 205 outputs a reference image stored in the frame memory to which the output end is connected among the frame memories FM1 to FMN of the frame memory 206, and inputs the reference image to the unidirectional motion compensation unit 203. In the decoding device 800, since the reference image is not used except for the prediction image generation unit 805, it is not necessary to output the reference image to the outside of the prediction image generation unit 805.

The unidirectional motion compensation unit 203 performs motion compensation prediction processing according to the prediction parameters input from the prediction parameter control unit 204 and the reference image input from the reference image selector 205, and generates a unidirectional prediction image. Since the motion compensation prediction has already been described with reference to FIG. 5, the description thereof will be omitted.

The unidirectional motion compensation unit 203 outputs a unidirectional prediction image and temporarily stores it in the memory 202. Here, when the motion information (prediction parameter) indicates bidirectional prediction, the multi-frame motion compensation unit 201 performs weighted prediction using two types of unidirectional prediction images, so that the unidirectional motion compensation unit 203 The first unidirectional prediction image corresponding to the first is stored in the memory 202, and the unidirectional prediction image corresponding to the second is directly output to the multi-frame motion compensation unit 201. Here, the unidirectional prediction image corresponding to the first is referred to as the first prediction image, and the unidirectional prediction image corresponding to the second is referred to as the second prediction image.

It should be noted that two unidirectional motion compensation units 203 may be prepared, and each may generate two unidirectional prediction images. In this case, when the motion information (prediction parameter) indicates unidirectional prediction, the unidirectional motion compensation unit 203 may directly output the first unidirectional prediction image as the first prediction image to the multi-frame motion compensation unit 201. Good.

The multi-frame motion compensation unit 201 uses the first prediction image input from the memory 202, the second prediction image input from the unidirectional motion compensation unit 203, and the WP parameter information input from the motion evaluation unit 109. A weighted prediction is performed to generate a prediction image. The multi-frame motion compensation unit 201 outputs a predicted image and inputs it to the addition unit 804.

Here, the details of the plurality of frame motion compensation units 201 will be described with reference to FIG. Like the predicted image generation unit 107, the multi-frame motion compensation unit 201 includes a default motion compensation unit 301, a weighted motion compensation unit 302, a WP parameter control unit 303, and WP selectors 304 and 305.

The WP parameter control unit 303 outputs the WP application flag and weight information based on the WP parameter information input from the index setting unit 806, inputs the WP application flag to the WP selectors 304 and 305, and weights the weight information. Input to the motion compensation unit 302.

Specifically, when the WP parameter information is input from the index setting unit 806, the WP parameter control unit 303 separates and outputs the WP parameter information into the first WP application flag, the second WP application flag, and the weight information. , The first WP application flag is input to the WP selector 304, the second WP application flag is input to the WP selector 305, and the weight information is input to the weighted motion compensation unit 302.

When the WP parameter information is input, the WP parameter control unit 303 checks whether the value of the weight information is within the specified range. For example, when w0C is expressed as a real value and LWD is 7, the first weighting coefficient is 384. Here, it is assumed that 384 is out of the range of the first weighting factor and cannot be used. In this case, since the WP parameter control unit 303 is data that violates the standard, the decoding control unit 807 may be notified of information indicating that the data violates the standard, and the decoding process may be stopped. Further, the WP parameter control unit 303 may perform the clipping process within the range of the first weighting coefficient and proceed with the decoding process. Further, the WP parameter control unit 303 may change the value of the first WP application flag from 1 to 0 to perform default motion compensation prediction.

The WP selectors 304 and 305 switch the connection end of each predicted image based on the WP application flag input from the WP parameter control unit 303. The WP selectors 304 and 305 connect their output ends to the default motion compensation unit 301 when their respective WP application flags are 0. Then, the WP selectors 304 and 305 output the first predicted image and the second predicted image and input them to the default motion compensation unit 301. On the other hand, the WP selectors 304 and 305 connect their output ends to the weighted motion compensation unit 302 when their respective WP application flags are 1. Then, the WP selectors 304 and 305 output the first predicted image and the second predicted image and input them to the weighted motion compensation unit 302.

The default motion compensation unit 301 performs average value processing based on the two unidirectional prediction images (first prediction image and second prediction image) input from the WP selectors 304 and 305, and generates a prediction image. Specifically, when the first WP application flag and the second WP application flag are 0, the default motion compensation unit 301 performs average value processing based on the mathematical formula (1).

When the prediction mode indicated by the motion information (prediction parameter) is unidirectional prediction, the default motion compensation unit 301 uses only the first prediction image to obtain the final prediction image based on the mathematical formula (4). calculate.

The weighted motion compensation unit 302 is based on the two unidirectional prediction images (first prediction image and second prediction image) input from the WP selectors 304 and 305 and the weight information input from the WP parameter control unit 303. Perform weighted motion compensation. Specifically, when the first WP application flag and the second WP application flag are 1, the weighted motion compensation unit 302 performs weighting processing based on the mathematical formula (7).

When the calculation accuracy of the first prediction image and the second prediction image is different from that of the prediction image, the weighted motion compensation unit 302 rounds the LWD, which is the fixed-point accuracy, by controlling it as in the mathematical formula (8). To realize.

Further, when the prediction mode indicated by the motion information (prediction parameter) is unidirectional prediction, the weighted motion compensation unit 302 uses only the first prediction image and the final prediction image based on the mathematical formula (9). Is calculated.

When the calculation accuracy of the first prediction image and the second prediction image is different from that of the prediction image, the weighted motion compensation unit 302 sets the fixed-point accuracy LWD as in the mathematical formula (8) as in the case of bidirectional prediction. The rounding process is realized by controlling to.

Since the fixed-point accuracy of the weighting coefficient has already been described with reference to FIG. 7, the description thereof will be omitted. In the case of unidirectional prediction, various parameters (second WP adaptation flag, second weighting coefficient, and second offset information) corresponding to the second prediction image are not used, so they are set to predetermined initial values. It may have been done.

The decoding unit 801 uses the syntax 500 shown in FIG. The syntax 500 shows the structure of the coded data to be decoded by the decoding unit 801. Since the syntax 500 has already been described with reference to FIG. 15, the description thereof will be omitted. Further, since the picture parameter set syntax 505 has already been described with reference to FIG. 16 except that the coding is decoding, the description thereof will be omitted. Further, the slice header syntax 507 has already been described with reference to FIG. 17, except that the coding is decoding, and thus the description thereof will be omitted. Further, the pread weight table syntax 508 has already been described with reference to FIG. 18, except that the coding is decoding, and thus the description thereof will be omitted.

Here, the details of the prediction method of each syntax element related to the weighted prediction in the syntax configuration will be described. The prediction of the syntax element is performed by the index reconstruction unit 801B. The syntax configuration that explicitly shows the prediction method of the second embodiment is the same as that of the first embodiment.

For the prediction method between the signals of luma_log2_weight_denom and chroma_log2_weight_denom indicating the fixed-point accuracy of the weighting coefficient, the restoration process is performed using the mathematical formula (13).

For the prediction methods of luma_weight_lx [i] and chroma_weight_lx [i] [j] representing the weight coefficients of the luminance and color difference signals, restoration processing is performed using mathematical formulas (16) and (19).

The plurality of prediction methods described above can be used not only individually but also in combination. For example, by combining the mathematical formula (13), the mathematical formula (15), the mathematical formula (19), and the like, it is possible to efficiently reduce the code amount of the syntax element in the index information.

As described above, in the second embodiment, the selection range of the weighting coefficient is derived and derived by allocating the values in the negative direction and the positive direction with the reference point of the weighting coefficient at which the pixel value change is 0 as substantially the center. Make sure that the weighting factor is within the selection range of the weighting factor. Therefore, according to the second embodiment, H. Compared with 264 and the like, the selection range of the weighting coefficient can be expanded, and it is possible to easily take the value on the positive side where the selection frequency is high. Further, according to the second embodiment, since the difference value of the weighting coefficient to be decoded is a signed 8-bit value from −128 to 127 as a fixed value, the signed 8 is expanded while expanding the selection range of the weighting coefficient. A selection range of bit precision can be specified.

As described above, in the second embodiment, since the range of the syntax (difference value of the weighting coefficient) to be decoded can be fixed, the decoder determines whether the decoded coded data is within the range of the predetermined specifications. Can be easily checked and the specifications can be simplified. For example, when the syntax to be decoded is a weighting coefficient and the selection range of the weighting coefficient fluctuates according to the reference value of the weighting coefficient, a table in which the reference value of the weighting coefficient and the minimum and maximum values of the selection range of the weighting coefficient are associated. It is necessary to prepare and refer to each time after deriving the selection range of the weighting factor. In such a case, it is necessary to load the table into the memory and refer to it each time, which increases the hardware scale. On the other hand, in the second embodiment, since the range of the syntax to be decoded (difference value of the weighting coefficient) can be fixed, the hardware scale can be reduced without being restricted by the hardware configuration as described above. Can be done.

Further, in the second embodiment, the difference value of the weighting coefficient whose range is fixed to the signed 8-bit accuracy is decoded, but the difference value of the weighting coefficient takes a value near the center of the range (near 0). , The code length at the time of decoding can be shortened, and the decoding efficiency can be improved. H. In 264 and the like, the weighting coefficient is decoded with a signed exponential Golomb code (se (v)), but this code is valid for a symbol whose value to be decoded exponentially increases with reference to 0. , The most frequently used reference value is generally the center of the range. In the second embodiment, the case where the pixel value change between pictures is 0 in a general moving image is set as the reference value of the weighting coefficient, and the prediction from the above-mentioned reference value is also introduced in the prediction of the selection range of the weighting coefficient. ing. As a result, the exponential Golomb code matches the selection range of the prediction and weighting coefficients, so the code amount reduction effect is high, and the coefficient range is determined around the reference value, so even if a large value is taken, it will be a positive value. The distance from the reference value of the negative value becomes about the same, and it has the effect of being able to decode with a shorter code length than the conventional method.

(Modification 1 of the first embodiment)
In the first embodiment, the derivation of the selection range of the weighting coefficient in the coding device 100 has been described, but in the modified example 1, the derivation of the selection range of the offset in the coding device 100 will be described.

As described in the formulas (20) to (22), in the color space of YUV, the color difference component expresses the color by the amount of deviation from the median value. Therefore, the amount of change from the pixel value change in consideration of the median value can be used as the predicted value by using the weighting coefficient. This predicted value shows the reference value of the offset when the influence of the weighting coefficient is excluded. That is, the index setting unit 108 can derive the offset selection range by allocating the range in which the value can be taken with the predicted value (offset reference value) as the substantially center, and the offset is included in the derived offset selection range. You can confirm that.

For example, when the LWD is 2 and the weighting coefficient value is 5, the weighting coefficient reference value is (1 << 2), that is, 4. On the other hand, since the value of the weighting coefficient is 5, the pixel value changes. Since the color difference signal expresses the color by the amount of deviation from the median, the index setting unit 108 obtains the offset reference value by eliminating the influence of the weighting coefficient. The offset reference value is formulated by the mathematical formula (23).

Pred = (MED − ((MED * chroma_weight_lx [i] [j]) >> chroma_log2_weight_denom))… (23)

Pred indicates the reference value of the offset of the color difference signal, MED indicates the median value of the color difference signal (128 at 8 bits), and the term on the right side means the amount of deviation from the median value due to the influence of the weighting coefficient. The mathematical formula (23) corresponds to a value obtained by inverting the sign of the rightmost term of the mathematical formula (20). As shown in the formula (23), the reference value of the offset of the color difference signal is determined according to the weighting coefficient and the fixed point accuracy of the color difference signal.

The mathematical formula (23) can be transformed like the mathematical formula (24).

Pred = ((1 << (BitDepth − 1)) − ((chroma_weight_lx [i] [j]) << (BitDepth − 1 − chroma_log2_weight_denom))… (24)

Here, BitDepth represents the pixel depth of the color difference signal, and if it is an 8-bit signal, BitDepth is 8. Since the MED of the mathematical formula (23) is a value expressed by a power of 2, it can be expressed as the mathematical formula (24) by rewriting the shift on the right side using BitDepth.

FIG. 21 is an explanatory diagram showing an example of a selection range of the offset of the color difference signal of the modification 1. In the example shown in FIG. 21, Pred is arranged so as to be located substantially in the center of the selection range, (Pred)-(1 << OR) is the minimum value of the selection range, and (Pred) + (1 << OR). ) -1 is the maximum value of the selection range. OR means the bit precision of the offset, for example, H. In 264 and the like, it becomes 8. As shown in FIG. 21, the selection range of the offset of the color difference signal is defined within a predetermined bit precision with the reference value of the offset of the color difference signal as a substantially center. Although detailed description is omitted, the difference value of the offset of the color difference signal to be encoded (the difference value between the offset of the color difference signal and the reference value of the offset of the color difference signal) is defined by a fixed value of the bit accuracy of the offset. it can. For example, with 8-bit precision, the offset difference value of the color difference signal is an 8-bit fixed value from −128 to 127. Further, for example, if the precision is 9 bits, the difference value of the offset of the color difference signal is a fixed 9-bit value of -256 to 255.

This solves the problem that the range of values to be encoded cannot be determined unless the reference value is restored. In the first modification, the index setting unit 108 describes the derivation of the offset selection range of the color difference signal, but the present invention is not limited to this, and the coding unit 110 may perform the derivation.

FIG. 22 is a flowchart showing an example of the derivation process of the offset selection range of the color difference signal of the modification 1. Here, the case where the index setting unit 108 performs the derivation process of the offset selection range of the color difference signal will be described, but as described above, the coding unit 110 may perform the process.

First, the index setting unit 108 derives the fixed-point precision LWD of the weighting coefficient (step S12). Here, the index setting unit 108 may derive the fixed-point precision LWD of the weighting coefficient from the WP parameter information or may derive it from the index information.

Subsequently, the index setting unit 108 derives the weighting coefficient Wxx (S13). Here, the index setting unit 108 may derive the weighting coefficient Wxx from the WP parameter information or may derive it from the index information.

Subsequently, the index setting unit 108 derives the reference value of the offset of the color difference signal from the mathematical formula (23) by using the fixed-point accuracy LWD of the derived weighting coefficient and the weighting coefficient Wxc (step S14).

Subsequently, the index setting unit 108 subtracts (1 << OR) from the derived reference value of the offset of the color difference signal to derive the minimum value of the offset selection range of the color difference signal (step S15).

Subsequently, the index setting unit 108 adds (1 << OR) -1 to the reference value of the offset of the derived color difference signal, and derives the maximum value of the offset selection range of the color difference signal (step S16).

Then, the index setting unit 108 confirms that the offset of the color difference signal is included in the selection range of the offset of the derived color difference signal. When the index setting unit 108 confirms that the offset of the color difference signal is not included in the offset selection range of the color difference signal, the index setting unit 108 performs clipping processing using the maximum value or the minimum value of the offset selection range of the color difference signal. May be done. In this case, the index setting unit 108 may clip at the minimum value if the offset of the color difference signal is smaller than the minimum value of the selection range, and clip at the maximum value if the offset of the color difference signal is larger than the maximum value of the selection range. Good. By introducing such a clip process, the value to be encoded such as the difference value of the offset of the color difference signal takes a value within a predetermined bit accuracy without setting a specific range constraint. The circuit scale configuration used by the hardware can be clarified.

As described with reference to FIG. 18, since the weighting coefficient value and the fixed-point accuracy information are encoded before the offset information, the weighting coefficient value can be derived when the offset reference value is derived. ..

Further, the selection range of the first offset and the second offset with respect to the color difference signal described in the first modification may be applied separately from the selection range of the first weighting coefficient and the second weighting coefficient described in the first embodiment. .. For example, the selection range of the first weighting factor and the second weighting factor is as follows. It is the same as 264, and the selection range of the first offset and the second offset with respect to the color difference signal may be the same as in the first modification.

According to the first modification, the range of the encoded syntax (offset difference value) can be fixed, so that the specification can be simplified as compared with the configuration in which the encoder dynamically changes these ranges. .. If the syntax to be decoded is an offset and the offset selection range fluctuates according to the offset reference value, prepare a table that associates the offset reference value with the minimum and maximum values of the offset selection range. It is necessary to have a configuration in which the offset selection range is referred to each time after derivation, or a configuration in which the offset selection range is calculated and derived each time. In such a case, a configuration in which the table is loaded into the memory and referenced each time and an arithmetic circuit for calculation are required, which increases the hardware scale. On the other hand, if the range of the encoding syntax (offset difference value) is fixed as in the first modification, the hardware scale can be reduced because the hardware configuration is not restricted.

(Modification 1 of the second embodiment)
In the second embodiment, the derivation of the selection range of the weighting coefficient in the decoding device 800 has been described, but in the first modification of the second embodiment, the derivation of the selection range of the offset in the decoding device 800 will be described. In the first modification of the second embodiment, the index setting unit 806 can derive a selection range of the offset by allocating a range in which the value can be taken with the predicted value (reference value of the offset) as a substantially center, and the offset is derived. It can be confirmed that it is included in the offset selection range. Since the derivation of the offset selection range is the same as that of the first modification of the first embodiment, detailed description thereof will be omitted. Further, the derivation of the offset selection range may be performed not by the index setting unit 806 but by the index reconstruction unit 801B.

According to the first modification of the second embodiment, the range of the encoded syntax (offset difference value) can be fixed, so that the decoder dynamically changes these ranges as compared with the configuration. Specifications can be simplified. If the syntax to be decoded is an offset and the offset selection range fluctuates according to the offset reference value, prepare a table that associates the offset reference value with the minimum and maximum values of the offset selection range. It is necessary to have a configuration in which the offset selection range is referred to each time after derivation, or a configuration in which the offset selection range is calculated and derived each time. In such a case, a configuration in which the table is loaded into the memory and referenced each time and an arithmetic circuit for calculation are required, which increases the hardware scale. On the other hand, if the range of the encoding syntax (offset difference value) is fixed as in the first modification, the hardware scale can be reduced because the hardware configuration is not restricted.

(Modification 2 of the first embodiment)
In the first embodiment, the derivation of the selection range of the weighting coefficient in the coding apparatus 100 has been described, but in the modification 2, the selection of the weighting coefficient in the derivation of the selection range of the weighting coefficient in the coding apparatus 100 An example of shifting the range will be described.

In the first embodiment, as described with reference to FIG. 9, the substantially center of the selection range of the weighting coefficient is used as the reference value of the weighting coefficient. Further, as described in FIG. 7 and the like, when there is no average pixel value change between images, the weighting coefficient value is 1.0 when expressed as a real value, and the range in which the weighting coefficient is negative is unidirectional. Not selected for weighted predictions. From this, it can be seen that the selection range of the weighting coefficient in actual operation has the highest selection frequency near the reference value, and the negative range is rarely used. Therefore, in the modification 2, the index setting unit 108 shifts the selection range of the weighting coefficient to the positive side when deriving the selection range of the weighting coefficient.

FIG. 23 is an explanatory diagram showing an example of the selection range of the weighting coefficient of the modified example 2. In the example shown in FIG. 23, unlike the selection range of the weighting coefficient described in FIG. 9, a new reference value ((1 << LWD) + SHFT) obtained by adding the shift value SHFT to the reference value (1 << LWD) of the weighting coefficient. ) Is located approximately in the center of the selection range, and the value obtained by subtracting 128 from this value (-128 + (1 << LWD) + SHFT) becomes the minimum value of the selection range, and 127 is added to this value. The value (127+ (1 << LWD) + SHFT) is the maximum value of the selection range. At this time, the maximum value may be larger than 255 depending on the value of the fixed-point precision LWD, but the index setting unit 108 may clip the maximum value at 255, or SHFT that can be taken for each fixed-point number. You may change the value of. In the second modification, an example in which the index setting unit 108 derives the selection range of the weighting coefficient has been described, but the present invention is not limited to this, and the coding unit 110 may perform the derivation.

FIG. 24 is a flowchart showing an example of the derivation process of the selection range of the weighting coefficient of the modification 2. Here, the description will be made on the assumption that the index setting unit 108 performs the derivation process of the selection range of the weighting coefficient, but as described above, the coding unit 110 may perform the process.

First, the index setting unit 108 derives the fixed-point precision LWD of the weighting coefficient (step S22). Here, the index setting unit 108 may derive the fixed-point precision LWD of the weighting coefficient from the WP parameter information or may derive it from the index information.

Subsequently, the index setting unit 108 derives a reference value ((1 << LWD) + SHFT) of the weighting coefficient by using the derived fixed-point precision LWD and shift value SHFT (step S23).

Subsequently, the index setting unit 108 subtracts 128 from the derived reference value of the weighting coefficient ((1 << LWD) + SHFT) to derive the minimum value of the selection range of the weighting coefficient (step S24).

Subsequently, the index setting unit 108 adds 127 to the derived reference value of the weighting coefficient ((1 << LWD) + SHFT), and derives the maximum value of the selection range of the weighting coefficient (step S25).

Then, the index setting unit 108 confirms that the weighting coefficient is included in the selected range of the derived weighting coefficient. When the index setting unit 108 confirms that the weighting coefficient is not included in the derived weighting coefficient selection range, the index setting unit 108 may perform clipping processing using the maximum value or the minimum value of the weighting coefficient selection range. Good. In this case, the index setting unit 108 may clip at the minimum value if the weighting coefficient is smaller than the minimum value of the selection range, and clip at the maximum value if the weighting coefficient is larger than the maximum value of the selection range. By introducing such a clip process, the value to be encoded such as the difference value of the weighting coefficient takes a value within a predetermined bit accuracy without setting a specific range constraint, so that the hardware Can clarify the configuration of the circuit scale used by.

As described above, in the modification 2, the selection range of the weighting coefficient is assigned in the negative direction and the positive direction centering on the reference point shifted by a predetermined value in consideration of the change in the weighting coefficient. Therefore, the range of values to be encoded can be fixed.

(Modification 2 of the second embodiment)
In the second embodiment, the derivation of the selection range of the weighting coefficient in the decoding device 800 has been described, but in the modification 2 of the second embodiment, the weight is derived when the selection range of the weighting coefficient in the decoding device 800 is derived. An example of shifting the selection range of the coefficient will be described. In the second modification of the second embodiment, the index setting unit 806 shifts the selection range of the weighting coefficient to the positive side when deriving the selection range of the weighting coefficient. Since the derivation of the selection range of the weighting coefficient is the same as that of the second modification of the first embodiment, detailed description thereof will be omitted. Further, the derivation of the selection range of the weighting coefficient may be performed not by the index setting unit 806 but by the index reconstruction unit 801B.

As described above, in the modified example 2 of the second embodiment, the negative direction and the positive direction are centered on the reference point in which the selection range of the weighting coefficient is shifted by a predetermined value in consideration of the change in the weighting coefficient. By allocating a value to, the range of values to be decoded can be fixed.

(Modification 3 of the first embodiment)
In the third modification, a derivation method different from the derivation method of the selection range of the weighting coefficient in the coding apparatus 100 of the first embodiment will be described.

In the third modification, luma_weight_lx [i] in the equations (14) to (16) has a fixed selection range, and delta_luma_weight_lx [i] has a dynamic selection range according to the LWD. The selection range of the weighting coefficient (luma_weight_lx [i]) of the modified example 5 is the same as that in FIG.

FIG. 25 is an explanatory diagram showing an example of the range of the difference value of the weighting coefficient of the coding target in the modified example 3. In the example shown in FIG. 25, the difference value of the weighting coefficient (delta_luma_weight_lx [i]) takes a signed 9-bit value in order to add or subtract a signed 8-bit signal. On the other hand, since the reference value of the weighting coefficient takes a value that increases according to the fixed-point precision, the difference value of the weighting coefficient tends to be biased to the negative side as the fixed-point precision value increases.

FIG. 26 is an explanatory diagram showing an example of the relationship between the values of the syntax elements of the modified example 3, and shows the relationship between the values of luma_log2_weight_denom, default_luma_weight_lx, luma_weight_lx [i], and delta_luma_weight_lx [i]. As shown in FIG. 19, the value of delta_luma_weight_lx [i], which is a syntax element encoded by the entropy coding unit 110A, that is, the range in which the difference value of the weighting coefficient can be taken becomes large, that is, the value of luma_log2_weight_denom representing fixed-point precision. It can be seen that there is a tendency to be biased toward the negative side. On the other hand, it can be seen that the value of the decoded weight coefficient (luma_weight_lx [i]) is in a fixed range from −128 to 127.

As described above, in the modified example 3, by defining the range of the difference value to be encoded so that the value of the decoded weight coefficient has a fixed selection range, even when the prediction method is changed, H. The same selection range as 264 can be defined.

(Modification 3 of the second embodiment)
In the third modification of the second embodiment, a derivation method different from the derivation method of the selection range of the weighting coefficient in the decoding device 800 of the second embodiment will be described. However, since the method for deriving the selection range of the weighting coefficient of the modified example 3 of the second embodiment is the same as that of the modified example 3 of the first embodiment, detailed description thereof will be omitted.

As described above, in the modified example 3 of the second embodiment, by defining the range of the difference value to be decoded so that the value of the weighting coefficient has a fixed selection range, even when the prediction method is changed, H. The same selection range as 264 can be defined.

(Modification 4 of the first embodiment)
In the fourth modification, an example of shifting the selection range of the weighting coefficient when deriving the selection range of the weighting coefficient of the third modification of the first embodiment will be described.

In the modified example 4, the index setting unit 108 shifts the range of the difference value of the weighting coefficient to the positive side, which is substantially equivalent to shifting the selection range of the weighting coefficient after decoding to the positive side. is there.

FIG. 27 is an explanatory diagram showing an example of the range of the difference value of the weighting coefficient of the modified example 4. Compared with the modified example 3 of the first embodiment, the range of the difference value of the weighting coefficient which takes the value in the 8-bit range from −128 to 127 is shifted to the positive side by SHFT.

FIG. 28 shows the selection range of the weighting coefficient after decoding of the modified example 4. From FIG. 28, it can be seen that in the modified example 4, the range of the weighting coefficient is shifted to the positive side by the amount of the shift of the difference value. Even with such a configuration, it becomes possible to select a reference value when the LWD is 7, which could not be selected in the past.

(Modification 4 of the second embodiment)
In the modified example 4 of the second embodiment, an example of shifting the selection range of the weighting coefficient when deriving the selection range of the weighting coefficient of the modified example 3 of the second embodiment will be described. However, since the method of shifting the selection range of the weighting coefficient of the modified example 4 of the second embodiment is the same as that of the modified example 4 of the first embodiment, detailed description thereof will be omitted. Even with such a configuration, it becomes possible to select a reference value when the LWD is 7, which could not be selected in the past.

(Modification 5 of the first embodiment)
In the modified example 5, an example in which the difference value of the weighting coefficient is wrapped in the modified example 3 and the modified example 4 of the first embodiment will be described.

As described with reference to FIG. 25, the difference value of the weighting coefficient is a signed 9-bit signal (-256 to 126), and is biased to the negative side as the fixed-point accuracy increases. Since the weighting coefficient is generally entropy-coded using an exponential Golomb code or the like, the coding efficiency may decrease if the positive / negative balance is unbalanced. The range of the difference value of the weighting coefficient differs depending on the fixed-point precision, but the range when the fixed-point precision is fixed is within 8 bits. For example, when LWD is 7, the range of the difference value is -256 to -1, and when shifted to the 0 reference, it becomes an 8-bit value from 0 to 255. Therefore, the index reconstruction unit 110B wraps the signed 9 bits into unsigned 8 bits according to the fixed-point precision. In this case, the positive value takes the conventional value and the negative value is connected to the end of the positive value.

FIG. 29 is a flowchart showing an example of wrapping processing of the difference value of the weighting coefficient of the modified example 5.

First, the index reconstruction unit 110B derives the fixed-point precision LWD of the weighting coefficient from the index information (step S32).

Subsequently, the index reconstruction unit 110B derives the weighting coefficient from the index information (step S33).

Subsequently, the index reconstruction unit 110B derives a reference value (1 << LWD) of the weighting coefficient by using the derived fixed-point precision LWD (step S34).

Subsequently, the index reconstruction unit 110B derives the difference value of the weighting coefficient from the mathematical formula (14) (step S35).

Subsequently, the index reconstruction unit 110B performs wrap processing based on the reference value (1 << LWD) of the weighting coefficient, and connects the negative value after the positive maximum value while keeping the positive value as it is. Generates an unsigned 8-bit code in (step S36).

Then, the code generated by the index reconstruction unit 110B is entropy-encoded by the entropy encoding unit 110A.

As described above, in the modified example 5, by performing the wrap processing on the signed 9-bit value, it becomes possible to always encode with the unsigned 8-bit, and the signed 9-bit exponential Golomb coding unit and the like can be used. Eliminates the need to have hardware.

(Modification 5 of the second embodiment)
In the modified example 5 of the second embodiment, an example of lapping the difference value of the weighting coefficient in the modified example 3 and the modified example 4 of the second embodiment will be described.

As described with reference to FIG. 25, the difference value of the weighting coefficient is a signed 9-bit signal (-256 to 126), and is biased to the negative side as the fixed-point accuracy increases. Since the weighting coefficient is generally entropy-coded using an exponential Golomb code or the like, the coding efficiency may decrease if the positive / negative balance is unbalanced. The range of the difference value of the weighting coefficient differs depending on the fixed-point precision, but the range when the fixed-point precision is fixed is within 8 bits. For example, when LWD is 7, the range of the difference value is -256 to -1, and when shifted to the 0 reference, it becomes an 8-bit value from 0 to 255. Therefore, the index reconstruction unit 801B wraps the signed 9 bits into the unsigned 8 bits according to the fixed-point precision. In this case, the positive value takes the conventional value and the negative value is connected to the end of the positive value.

FIG. 30 is a flowchart showing an example of restoration processing of the difference value of the weighting coefficient of the modified example 5 of the second embodiment.

First, the entropy decoding unit 801A decodes the coded data to derive the fixed-point precision LWD of the weighting coefficient (step S42).

Subsequently, the entropy decoding unit 801A decodes the coded data and decodes the unsigned 8-bit code indicating the difference value of the weighting coefficient (step S43).

Subsequently, the index reconstruction unit 801B derives a reference value (1 << LWD) of the weighting coefficient by using the derived fixed-point precision LWD (step S44).

Subsequently, the index reconstruction unit 801B restores the unsigned 8-bit code to a signed 9-bit difference value using the derived weight coefficient reference value (1 << LWD) (step S45). Here, the difference value is restored by leaving the value below the reference value as it is from the decoded data and connecting the code above the reference value to the negative side. From the above, the difference value of the restored weighting coefficient is derived, and the weighting coefficient is restored by the mathematical formula (15).

As described above, in the modified example 5 of the second embodiment, by performing the wrap processing on the signed 9-bit value, it becomes possible to always encode with the unsigned 8-bit, and the signed 9-bit exponential Golomb. It is no longer necessary to have hardware such as an encoding unit.

(Modification 6)
In the first and second embodiments, an example is described in which a frame is divided into rectangular blocks having a size of 16 × 16 pixels, and coding / decoding is performed in order from the block on the upper left of the screen to the lower right (FIG.). See 2A). However, the coding order and decoding order are not limited to this example. For example, coding and decoding may be performed in order from the lower right to the upper left, or coding and decoding may be performed so as to draw a spiral from the center of the screen toward the edge of the screen. Further, coding and decoding may be performed in order from the upper right to the lower left, or coding and decoding may be performed so as to draw a spiral from the edge of the screen toward the center of the screen. In this case, since the position of the adjacent pixel block that can be referred to changes depending on the coding order, it may be changed to a position that can be used as appropriate.

In the first and second embodiments, the prediction target block sizes such as 4 × 4 pixel block, 8 × 8 pixel block, and 16 × 16 pixel block have been illustrated and described, but the prediction target block is a uniform block. It does not have to be a shape. For example, the prediction target block size may be a 16 × 8 pixel block, an 8 × 16 pixel block, an 8 × 4 pixel block, a 4 × 8 pixel block, or the like. Further, it is not necessary to unify all block sizes in one coding tree block, and a plurality of different block sizes may be mixed. When a plurality of different block sizes are mixed in one coding tree block, the amount of code for encoding or decoding the division information increases as the number of divisions increases. Therefore, it is desirable to select the block size in consideration of the balance between the code amount of the divided information and the quality of the locally decoded image or the decoded image.

In the first and second embodiments, for the sake of simplification, there is a part in which a comprehensive explanation regarding the color signal component is described without distinguishing between the prediction processing in the luminance signal and the color difference signal and the method for deriving the selection range. .. However, when the prediction process and the method for deriving the selection range are different between the luminance signal and the color difference signal, the same or different prediction methods may be used. If different prediction methods are used for the luminance signal and the color difference signal, the prediction method selected for the luminance signal can be encoded or decoded in the same manner as the luminance signal.

In the first and second embodiments, for the sake of simplification, a comprehensive description of the color signal component is described without distinguishing between the luminance signal and the weighted motion compensation prediction process in the color difference signal. However, when the weighted motion compensation prediction processing differs between the luminance signal and the color difference signal, the same or different weighted motion compensation prediction processing may be used. If different weighted motion compensation prediction processes are used between the luminance signal and the color difference signal, the weighted motion compensation prediction process selected for the color difference signal can be encoded or decoded in the same manner as the luminance signal.

In the first and second embodiments, it is possible to insert a syntax element not specified in the present embodiment between the rows of the table shown in the syntax configuration, and other descriptions regarding conditional branching are included. It doesn't matter if it is. Alternatively, the syntax table can be divided and integrated into a plurality of tables. Further, it is not always necessary to use the same term, and it may be arbitrarily changed depending on the form to be used.

As described above, in each embodiment and each modification, a range of possible values of the syntax element is defined when performing weighted motion compensation prediction, and a range of values associated therewith is within a predetermined bit accuracy range. By setting and giving a short code length to a value that is actually frequently used, highly efficient weighted motion compensation prediction processing can be performed while solving the problem of encoding redundant information of syntax elements. Realize. Therefore, according to each embodiment and each modification, the coding efficiency is improved, and the subjective image quality is also improved.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other embodiments, and various omissions, replacements, and changes can be made without departing from the gist of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are also included in the scope of the invention described in the claims and the equivalent scope thereof.

For example, it is also possible to provide a program that realizes the processing of each of the above embodiments by storing it in a computer-readable storage medium. The storage medium may be a storage medium such as a magnetic disk, an optical disk (CD-ROM, CD-R, DVD, etc.), an optical magnetic disk (MO, etc.), a semiconductor memory, etc., which can store a program and can be read by a computer. For example, the storage form may be any form.

Further, the program that realizes the processing of each of the above embodiments may be stored on a computer (server) connected to a network such as the Internet and downloaded to the computer (client) via the network.

100 Coding device 101 Subtraction unit 102 Orthogonal conversion unit 103 Quantization unit 104 Inverse quantization unit 105 Inverse orthogonal conversion unit 106 Addition unit 107 Prediction image generation unit 108 Index setting unit 109 Motion evaluation unit 110 Coding unit 110A Entropy coding unit 110B Index reconstruction unit 111 Coding control unit 201 Multiple frame motion compensation unit 202 Memory 203 Unidirectional motion compensation unit 204 Prediction parameter control unit 205 Reference image selector 206 Frame memory 207 Reference image control unit 301 Default motion compensation unit 302 Weighted motion Compensation unit 303 WP parameter control unit 304, 305 WP selector 800 Decoding device 801 Decoding unit 801A Entropy decoding unit 801B Index reconstructing unit 802 Inverse quantization unit 803 Inverse orthogonal conversion unit 804 Addition unit 805 Prediction image generation unit 806 Index setting unit 807 Decoding control unit

Claims (3)

The data representing the first fixed-point precision of the weighting coefficients of luminance used in weighted motion compensated prediction on images,
The data representing the first difference value, which is the same value as the difference between the first fixed-point accuracy and the second fixed-point accuracy of the color difference weighting coefficient used in the weighted motion compensation prediction, is the first. Data to be used in the process of determining the second fixed-point accuracy by adding the fixed-point accuracy and the first difference value, and
It is the same value as the difference between the first reference value, which is the same value as the value obtained by shifting "1" to the left by the number of bits determined by the first fixed-point precision, and the weighting coefficient of the brightness. The data representing the second difference value of the weighting coefficient of the brightness, which is a value that can take a range from −128 to +127 regardless of the first fixed-point precision, and is the first reference value and the second. By adding the difference value, the data to be used in the process of determining the weighting coefficient of the brightness and the data
And a coding unit that generates coded data that encodes each of
A storage unit that stores the coded data and
A storage device comprising. The data representing the first fixed-point precision of the weighting coefficients of luminance used in weighted motion compensated prediction on images,
The data representing the first difference value, which is the same value as the difference between the first fixed-point accuracy and the second fixed-point accuracy of the color difference weighting coefficient used in the weighted motion compensation prediction, is the first. Data to be used in the process of determining the second fixed-point accuracy by adding the fixed-point accuracy and the first difference value, and
It is the same value as the difference between the first reference value, which is the same value as the value obtained by shifting "1" to the left by the number of bits determined by the first fixed-point precision, and the weighting coefficient of the brightness. , The data representing the second difference value of the weighting coefficient of the brightness, which is a value that can take a range from −128 to +127 regardless of the first fixed-point precision, and is the first reference value and the second. By adding the difference value, the data to be used in the process of determining the weighting coefficient of the brightness and the data
And a coding unit that generates coded data that encodes each of
A transmitter that transmits the coded data and
A transmitter equipped with. The data representing the first fixed-point precision of the weighting coefficients of luminance used in weighted motion compensated prediction on images,
The data representing the first difference value, which is the same value as the difference between the first fixed-point accuracy and the second fixed-point accuracy of the color difference weighting coefficient used in the weighted motion compensation prediction, is the first. Data to be used in the process of determining the second fixed-point accuracy by adding the fixed-point accuracy and the first difference value, and
It is the same value as the difference between the first reference value, which is the same value as the value obtained by shifting "1" to the left by the number of bits determined by the first fixed-point precision, and the weighting coefficient of the brightness. The data representing the second difference value of the weighting coefficient of the brightness, which is a value that can take a range from −128 to +127 regardless of the first fixed-point precision, and is the first reference value and the second. By adding the difference value, the data to be used in the process of determining the weighting coefficient of the brightness and the data
And the receiver that receives the coded data, respectively .
A decoding unit that decodes the coded data,
A receiver equipped with.

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