JP6744507B2 - Encoding method and decoding method - Google Patents

Description

Embodiments of the present invention relate to an encoding method, a decoding method, and encoded data.

In recent years, an image coding method with greatly improved coding efficiency has been proposed by ITU-T in cooperation with International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC). TREC. H. H.264 and ISO/IEC 14496-10 (hereinafter referred to as “H.264”).

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

Further, a method of encoding a moving image including a fade effect or a dissolve effect with higher efficiency than the inter-prediction encoding method in ISO/IEC MPEG (Moving Picture Experts Group)-1, 2, 4 has been proposed. In this method, as a framework for predicting a change in lightness in the time direction, fractionally accurate motion-compensated prediction is performed on an input moving image having luminance and two color differences. Then, using the index indicating the combination including the reference image, the weighting coefficient for each of the brightness and the two color differences, and the offset for each of the brightness and the two color differences, the predicted image is multiplied by the weighting coefficient and the offset is added.

JP 2004-7377 A

However, in the conventional technique as described above, since the index is coded as a direct value, the coding efficiency is reduced. The problem to be solved by the present invention is to provide an electronic device, a decoding method and a program capable of improving the coding efficiency.

The encoding method of the embodiment relates to a reference image, a luminance weighting factor, a first fixed point precision of the luminance weighting factor, a color difference weighting factor, and a second fixed point precision of the color difference weighting factor. The same as the difference between the first fixed-point precision and the second fixed-point precision; the step of setting the index of the first fixed-point precision; the step of encoding one of the first fixed-point precision and the second fixed-point precision; A step of encoding a first difference value, which is a value, and the same value as the value obtained by left-shifting "1" by the number of bits determined by the first fixed-point precision, and wherein the reference image A first reference value that is the same value as the value of the weighting coefficient of the color difference when the pixel value change in the color difference between the target image and the target image is less than or equal to a specific reference is derived based on the first fixed-point precision. And a step of encoding a second difference value of the luminance weighting coefficient, which is the same value as the difference between the first reference value and the luminance weighting coefficient, and is determined by the second fixed-point precision. Weight of the color difference when the pixel value change between the reference image and the target image is equal to or less than a specific reference value, which is the same as the value obtained by left-shifting "1" by the number of bits A step of deriving a second reference value that is the same value as the coefficient value based on the second fixed point precision, and a value that is the same as the difference between the color difference weighting coefficient and the second reference value, Encoding the difference value.

The block diagram which shows the example of the encoding apparatus of 1st Embodiment. FIG. 3 is an explanatory diagram showing an example of a predictive coding order of pixel blocks in the first 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. FIG. 3 is a block diagram showing an example of a predicted image generation unit according to the first embodiment. The figure which shows the example of the relationship of the motion vector of the motion compensation prediction in bidirectional prediction of 1st Embodiment. The block diagram which shows the example of the multi-frame motion compensation part of 1st Embodiment. Explanatory drawing of the example of the fixed point precision of the weighting coefficient in 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 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 pread weight table syntax of 1st Embodiment. The figure which shows the example of the syntax structure which showed the prediction method of 1st Embodiment explicitly. The flowchart which shows the prediction processing example of fixed point precision of 1st Embodiment. 6 is a flowchart illustrating an example of fixed point precision restoration processing according to the first embodiment. 6 is a flowchart showing an example of weighting coefficient prediction processing according to the first embodiment. 6 is a flowchart showing an example of weighting coefficient restoration processing according to the first embodiment. The flowchart which shows the other example of the prediction process of the weighting coefficient of 1st Embodiment. The flowchart which shows the other example of the restoration process of the weighting coefficient of 1st Embodiment. 5 is a flowchart showing an example of color difference signal prediction processing according to the first embodiment. 6 is a flowchart showing an example of color difference signal restoration processing according to the first embodiment. The flowchart which shows the other example of the prediction process example of the weighting coefficient of 1st Embodiment. 9 is a flowchart showing another example of the restoration processing example of the weighting factor of the first embodiment. The block diagram which shows the structural example of the decoding apparatus of 2nd Embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. The encoding device and the 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). In addition, the encoding device and the decoding device of each of the following embodiments can be realized by causing a computer to execute a program, that is, software. Note that 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, an encoding device that encodes a moving image will be described.

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

The encoding apparatus 100 divides each frame or each field forming an input image into a plurality of pixel blocks, and uses a coding parameter input from the coding control unit 111, to predictively code the divided pixel blocks. Conversion to generate a predicted image. Then, the encoding device 100 subtracts the input image and the predicted image divided into a plurality of pixel blocks to generate a prediction error, orthogonally transforms and quantizes the generated prediction error, and further performs entropy coding to perform coding. Generate and output data.

The coding apparatus 100 performs predictive coding by selectively applying a plurality of prediction modes in which at least one of the block size of a pixel block and the method of generating a predicted image is different. The methods of generating the predicted image are roughly classified into two types: intra prediction that performs prediction within the encoding target frame and inter prediction that performs motion compensation prediction using one or more temporally different reference frames. Intra prediction is also referred to as intra-picture prediction or intra-frame prediction, and inter-prediction is also referred to as inter-picture prediction, inter-frame prediction, motion compensation prediction, or the like.

FIG. 2 is an explanatory diagram showing an example of a predictive coding order of pixel blocks in the first embodiment. In the example illustrated in FIG. 2, the encoding device 100 performs the predictive encoding from the upper left to the lower right of the pixel block, and in the frame f to be encoded, the left side and the left side of the encoding target pixel block c. The encoded pixel block p is located on the upper side. In the following, for simplification of description, the coding apparatus 100 performs the predictive coding in the order shown in FIG. 2, but the predictive coding order 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 to mean a coding tree block, but it may be used to have another meaning. 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, a block may be 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 a block size of a coding tree block in the first embodiment. The coding tree block is typically a 64×64 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 illustrating specific examples of the coding tree block according to the first embodiment. FIG. 3B shows a coding tree block having a block size of 64×64 (N=32). N represents the size of a coding tree block serving as a reference, and the size when divided is defined as N, and the size when not divided is defined as 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.

Note that the coding tree block can be further quadtree-divided within one quadtree number. This allows the coding tree block to be hierarchically divided. 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 has a block size of 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 this unit in raster scan order.

In the following description, a coding target block or a coding tree block of an 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 encoding device 100 includes a subtraction unit 101, an orthogonal transformation unit 102, a quantization unit 103, an inverse quantization unit 104, an inverse orthogonal transformation unit 105, an addition unit 106, and a prediction unit. An image generation unit 107, an index setting unit 108, a motion evaluation unit 109, and an encoding unit 110 are provided. The coding control unit 111 illustrated in FIG. 1 controls the coding device 100, and can be realized by, for example, a CPU (Central Processing Unit).

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 the prediction error and inputs it to the orthogonal transformation 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 transform coefficients. The orthogonal transformation unit 102 outputs the transformation coefficient and inputs it to the quantization unit 103.

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

The inverse quantization unit 104 performs inverse quantization processing on the quantized transform coefficient input from the quantization unit 103 to obtain a restored transform coefficient. Specifically, the inverse quantization unit 104 performs inverse quantization according to the quantization information used in the quantization unit 103. More specifically, the dequantization unit 104 multiplies the quantized transform coefficient by the quantized step size derived from the quantized information to obtain the restored transformed coefficient. The quantization information used in the quantization unit 103 is loaded from an internal memory (not shown) of the encoding control unit 111 and used. The inverse quantization unit 104 outputs the restoration transform coefficient and inputs it to the inverse orthogonal transform 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 quantization unit 104, Get the reconstruction 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 predicted image to generate a locally decoded image. The addition unit 106 outputs the locally decoded image and inputs it to the predicted image generation unit 107.

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

FIG. 4 is a block diagram showing an example of the configuration of the predicted image generation unit 107 according to the first embodiment. As shown in FIG. 4, the predicted image generation unit 107 includes a multiple 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 a 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≧2) for temporarily holding a reference image.

The prediction parameter control unit 204 prepares a plurality of combinations of reference image numbers and prediction parameters as a table based on the motion information input from the motion evaluation unit 109. Here, the motion information refers to a motion vector used for motion compensation prediction, a reference image number, information about 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 to generate the prediction image based on the input image, inputs the reference image number to the reference image selector 205, and outputs the prediction parameter. Is input to the unidirectional motion compensation unit 203.

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

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

FIG. 5: is a figure which shows an example of the relationship of the motion vector of the motion compensation prediction in the bidirectional prediction of 1st Embodiment. In motion compensation prediction, interpolation processing is performed using a reference image, and a unidirectional prediction image is generated based on the amount of motion shift from the pixel block at the encoding target position between the created interpolation image and the input image. .. Here, the shift amount is a motion vector. As shown in FIG. 5, in a bidirectional prediction slice (B-slice), a predicted image is generated using two types of reference images and a set of motion vectors. As the interpolation processing, interpolation processing with 1/2 pixel accuracy, interpolation processing with 1/4 pixel accuracy, or the like is used, and the value of the interpolation image is generated by performing the filtering processing on the reference image. For example, H.264 capable of performing interpolation processing up to ¼ pixel accuracy for a luminance signal. In H.264, the shift amount is represented by four times the integer pixel precision.

The unidirectional predictive motion compensation unit 203 outputs the unidirectional predicted 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 unidirectionally predicted images, so the unidirectionally predicted motion compensation unit 203. Stores the unidirectional predicted image corresponding to the first in the memory 202, and directly outputs the unidirectional predicted image corresponding to the second to the multi-frame motion compensation unit 201. Here, the unidirectionally predicted image corresponding to the first is the first predicted image, and the unidirectionally predicted image corresponding to the second is the second predicted image.

It should be noted that two unidirectional motion compensation units 203 may be prepared and each may generate two unidirectional predicted images. In this case, if the motion information (prediction parameter) indicates unidirectional prediction, the unidirectional motion compensating unit 203 may directly output the first unidirectional predicted image as the first predicted image to the multi-frame motion compensating 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 prediction motion compensation unit 203, and the WP parameter information input from the motion evaluation unit 109. , Weighted prediction is performed to generate a predicted image. The multi-frame motion compensation unit 201 outputs the 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. It is input to the motion compensation unit 302.

Here, the WP parameter information includes the fixed point precision of the weighting factor, the first WP application flag corresponding to the first prediction image, the first weighting factor, and the first offset, and the second WP adaptation corresponding to the second prediction image. It includes information on a flag, a second weighting factor, and a second offset. The WP application flag is a parameter that can be set for each corresponding reference image and signal component, and indicates whether to perform weighted motion compensation prediction. The weight information includes fixed-point precision of the weight coefficient, first weight coefficient, first offset, second weight coefficient, and second offset information.

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 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.

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. When each WP application flag is 0, the WP selectors 304 and 305 connect each output terminal to the default motion compensation unit 301. 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 the respective output ends to the weighted motion compensation unit 302 when the 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 unidirectionally predicted images (first predicted image and second predicted image) input from the WP selectors 304 and 305, and generates a predicted image. Specifically, when the first WP application flag and the second WP application flag are 0, the default motion compensation unit 301 performs the average value process based on Expression (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 process, and are determined by the internal calculation accuracy of the first predicted image and the second predicted image. If 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 Formula (2) and offset2 is formulated by Formula (3). To be done.

shift2=(M−L+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 Equation (2) and offset2=(1<< from Equation (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 calculate the final prediction image based on Expression (4). calculate.

P[x,y]=Clip1((PLX[x,y]+offset1)>>(shift1)) (4)

Here, PLX[x, y] indicates a unidirectional predicted image (first predicted 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 for rounding processing, and are determined by the accuracy of the internal calculation of the first predicted image. If the bit precision of the predicted image is L and the bit precision of the first predicted image is M, shift1 is formulated by equation (5) and offset1 is formulated by equation (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 Formula (5) and offset1=(1<<5) from 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. Specifically, 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 Expression (7).

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

Here, w0C represents a weighting coefficient corresponding to the first prediction image, w1C represents a weighting coefficient corresponding to the second prediction image, o0C represents an offset corresponding to the first prediction image, and o1C represents an offset corresponding to the second prediction image. .. Hereinafter, each is called a first weighting coefficient, a second weighting coefficient, a first offset, and a second offset. logWDC is a parameter indicating the fixed point precision of each weighting factor. The variable C means a signal component. For example, in the case of a YUV space signal, the luminance signal is C=Y, the Cr color difference signal is C=Cr, and the Cb color difference component is C=Cb.

Note that the weighted motion compensation unit 302 controls the logWDC, which is fixed-point precision, as in Equation (8) when the first prediction image and the second prediction image have different calculation precisions from each other, thereby performing a rounding process. To realize.

logWD'C=logWDC+offset1 (8)

The rounding process can be realized by replacing the logWDC in Expression (7) with logWD′C in Expression (8). 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, by resetting logWDC, the calculation precision similar to shift2 in the equation (1) is obtained. It is possible to realize a batch rounding process.

Note that 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 Expression (9). To calculate.

P[x,y]=Clip1((PLX[x,y]*wXC+(1<<logWDC-1))>>(logWDC)) (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 show. For example, when the reference list is 0, PL0[x, y] and w0C, and when the reference list is 1, PL1[x, y] and w1C.

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

The rounding process can be realized by replacing the logWDC in Expression (7) with logWD′C in Expression (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 logWDC, a batch rounding process with the same calculation precision as shift1 in Formula (4) is realized. It becomes possible to do.

FIG. 7 is an explanatory diagram of an example of fixed-point precision of the weighting factor in the first embodiment, and is a diagram illustrating an example of a change in a moving image having a brightness change in the time direction and a gradation value. In the example shown in FIG. 7, the encoding target frame is set to Frame(t), the temporally previous frame is set to Frame(t−1), and the temporally subsequent frame is set to Frame(t+1). As shown in FIG. 7, in a faded image that changes from white to black, the brightness (gradation value) of the image decreases with time. The weighting coefficient means the degree of change in FIG. 7, and takes a value of 1.0 when there is no change in lightness, as is clear from Expressions (7) and (9). The fixed point precision is a parameter that controls the step size corresponding to the decimal point of the weighting coefficient, and the weighting coefficient when the brightness does not change is 1<<logWDC.

Note that, in the case of unidirectional prediction, various parameters (second WP adaptation flag, second weighting coefficient, and second offset information) corresponding to the second predicted image are not used, so set to a predetermined initial value. It may have been done.

Returning to FIG. 1, the motion evaluation unit 109 performs motion evaluation between a plurality of frames based on the input image and the reference image input from the predicted image generation unit 107, outputs motion information and WP parameter information, and outputs the motion information. The prediction image generation unit 107 and the encoding unit 110 are input, 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 using a plurality of reference images corresponding to the same position as the input image of the prediction target pixel block as a starting point, calculates the error, shifts this position with fractional accuracy, and calculates the minimum error. Optimal motion information is calculated by a method such as block matching that searches for the block. In the case of bidirectional prediction, the motion evaluation unit 109 uses the motion information derived by unidirectional prediction to perform block matching including default motion-compensated prediction as shown in Expressions (1) and (4). By doing so, the bidirectional prediction motion information is calculated.

At this time, the motion evaluation unit 109 can calculate the WP parameter information by performing block matching including weighted motion-compensated prediction as shown in Expressions (7) and (9). Note that the WP parameter information may be calculated by using a method of calculating a weighting coefficient or offset using the brightness gradient of the input image, or a method of calculating a weighting coefficient or offset by accumulating prediction errors at the time of encoding. Good. Further, the WP parameter information may use a fixed value determined in advance for each encoding device.

Here, a method of calculating a weighting coefficient, a fixed-point precision of the weighting coefficient, and an offset from a moving image whose brightness changes temporally will be described with reference to FIG. 7. As described above, in the faded image that changes from white to black as shown in FIG. 7, the brightness (gradation value) of the image decreases with time. The motion evaluation unit 109 can calculate the weighting coefficient by calculating this inclination.

Further, the fixed point precision of the weighting factor is information indicating the precision 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 in image brightness. For example, in FIG. 7, when the weighting factor between Frame(t-1) and Frame(t+1) is 0.75 in decimal point precision, 3/4 precision can be expressed as 3/4, and therefore motion estimation The 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 fixed value determined in advance.

When the inclinations 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 weighting factor between Frame(t−1) and Frame(t+1) is 0.60 in decimal point precision and the fixed point precision is 1 (1<<1), the weighting factor is 1. (That is, the decimal point precision of the weighting coefficient is 0.50) is likely to be set. 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 a correction value for this amount from the maximum value of the pixels and sets it as an offset value. Set. When the maximum value of pixels is 255, the motion evaluation unit 109 may set a value such as 25 (255×0.1).

In addition, in the first embodiment, the motion evaluation unit 109 is illustrated as one function of the encoding device 100, but the motion evaluation unit 109 is not an essential configuration of the encoding device 100, and, for example, the motion evaluation unit 109 is encoded. It may be a device other than the processing 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 encoding 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 it to the encoding 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 below to generate index information.

8A and 8B are diagrams illustrating an example of WP parameter information according to the first embodiment. An example of the WP parameter information at the time of P-slice is as shown in FIG. 8A, and an example of the WP parameter information at the time of B-slice is as shown in FIG. 8A and FIG. 8B. The list number is an identifier indicating a prediction direction, and has a value of 0 during unidirectional prediction and two types of predictions during bidirectional prediction, and thus takes two values of 0 and 1. 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 each reference image, the information required for B-slice is 2N when the number of reference images is N.

Returning to FIG. 1, the encoding unit 110 includes a quantized transform coefficient input from the quantization unit 103, motion information input from the motion evaluation unit 109, index information input from the index setting unit 108, and encoding control. Encoding processing is performed on various encoding parameters such as quantization information designated by the unit 111 to generate encoded data. The encoding process corresponds to, for example, Huffman encoding or arithmetic encoding.

The coding parameter is a parameter required for decoding prediction information indicating a prediction method and the like, information regarding a quantized transform coefficient, and information regarding quantization. For example, the encoding control unit 111 has an internal memory (not shown), the encoding parameters are held in this internal memory, and the encoding parameters of the adjacent already encoded pixel blocks are used when encoding the pixel blocks. You can For example, H.264. In H.264 intra prediction, the prediction information of the pixel block can be derived from the prediction information of the encoded adjacent block.

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

The coding unit 110 includes an entropy coding unit 110A and an index reconstructing 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.264. In H.264, context-based variable length coding (CAVLC) and context-based adaptive coding (CABAC) 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 reconstructing unit 110B performs prediction processing according to the characteristics of the parameter of the syntax element, and the value of the syntax element as it is (direct (Value) and the difference value between the prediction values and outputs it to the entropy coding unit 110A. A specific example of the prediction process will be described later.

FIG. 9 is a diagram showing an example of the syntax 500 used by the encoding device 100 of the first embodiment. The syntax 500 indicates the structure of encoded data generated by the encoding device 100 encoding the input image (moving image data). When decoding the encoded data, the decoding device described below refers to the same syntax structure as the syntax 500 to perform syntax interpretation of the moving image.

The syntax 500 includes three parts, a high level syntax 501, a slice level syntax 502, and a coding tree level syntax 503. The high level syntax 501 includes syntax information of a layer higher than the slice. A slice refers to a rectangular area or a continuous area included in a frame or field. Slice level syntax 502 contains the information needed to decode each slice. The coding tree level syntax 503 includes information necessary for decoding each coding tree (that is, 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 pread weight table syntax 508, a slice data syntax 509, and the like. The pread 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 may 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 transform and quantization. Information about weighted motion-compensated prediction may be described in these syntaxes.

FIG. 10 is a diagram showing an example of the picture parameter set syntax 505 of the first embodiment. weighted_pred_flag is, for example, a syntax element indicating valid or invalid of the weighted compensation prediction of the first embodiment regarding P-slice. When weighted_pred_flag is 0, the weighted motion-compensated prediction in the first embodiment in P-slice is 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 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.

Note that 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 weighted motion-compensated prediction of one embodiment may be defined as valid or invalid.

weighted_bipred_idc is, for example, a syntax element indicating validity or invalidity of the weighted compensation prediction of the first embodiment regarding B-slice. When weighted_bipred_idc is 0, the weighted motion-compensated prediction in the first embodiment in B-slice is 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 output ends to the default motion compensation unit 301. On the other hand, when weighted_bipred_idc is 1, the weighted motion compensation prediction in the B-slice of the first embodiment is effective.

As another example, when weighted_bipred_idc is 1, in the syntax of a lower layer (slice header, coding tree block, transform unit, etc.), the local area inside the slice is different from that of the first embodiment. The weighted motion compensation prediction may be defined as valid or invalid.

FIG. 11 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.). pic_parameter_set_id is an identifier indicating which picture parameter set syntax 505 is referred to. num_ref_idx_active_override_flag is a flag indicating whether or not the number of valid reference images is updated. 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 pread weight table syntax used for weighted motion compensation prediction, and when weighted_pred_flag is 1 and P-slice, and when weighted_bipred_idc is 1 and B-slice, this function is Be called.

FIG. 12 is a diagram showing an example of the pread weight table syntax 508 according to the first embodiment. luma_log2_weight_denom represents the fixed point precision of the weighting factor of the luminance signal in the slice, and is a value corresponding to logWDC in Expression (7) or Expression (9). chroma_log2_weight_denom represents the fixed point precision of the weighting coefficient of the color difference signal in the slice, and is a value corresponding to logWDC in Expression (7) or Expression (9). chroma_format_idc is an identifier indicating a color space, and MONO_IDX is a value indicating a monochrome image. num_ref_common_active_minus1 indicates a 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 WP adaptation flags in the luminance signal corresponding to each of list 0 and list 1. When this flag is 1, the weighted motion-compensated prediction of the luminance signal of the first embodiment is effective in the entire 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 signals of the first embodiment is effective in the entire slice. luma_weight_l0[i] and luma_weight_l1[i] are weighting coefficients of the i-th luminance signal managed in each of list 0 and list 1. luma_offset_l0[i] and luma_offset_l1[i] are the offsets of the i-th luminance signal managed in each of the list 0 and the list 1. These are the values corresponding to w0C, w1C, o0C, and o1C in Expression (7) or Expression (9), respectively. However, C=Y.

chroma_weight_l0[i][j] and chroma_weight_l1[i][j] are weighting coefficients of the i-th corresponding color difference signal managed in list 0 and list 1, respectively. chroma_offset_l0[i][j] and chroma_offset_l1[i][j] are the offsets of the ith color-difference signal managed in list 0 and list 1, respectively. These are the values corresponding to w0C, w1C, o0C, and o1C in Expression (7) or Expression (9), respectively. However, C=Cr or Cb. j indicates a component of a color difference component, and in the case of a YUV 4:2:0 signal, for example, j=0 indicates a Cr component and j=1 indicates a Cb component.

Here, the details of the method of predicting 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 reconstructing unit 110B. FIG. 13 is a diagram showing an example of a syntax configuration explicitly showing the prediction method of the first embodiment. In the example shown in FIG. 13, the syntax elements to which prediction is introduced are shown with a prefix of delta, but these syntax configurations basically have the same configuration elements as the syntax configuration shown in FIG.

First, a method of predicting between the signals of luma_log2_weight_denom and chroma_log2_weight_denom indicating the fixed point precision of the weight coefficient will be described. The index reconstructing unit 110B performs the prediction process between the signals of luma_log2_weight_denom and chroma_log2_weight_denom using the mathematical formula (10), and performs the restoration process using the mathematical formula (11). Here, as shown in FIGS. 12 and 13, 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) (10)

chroma_log2_weight_denom = (luma_log2_weight_denom + delta_chroma_log2_weight_denom) (11)

FIG. 14 is a flowchart showing an example of the chroma_log2_weight_denom prediction process of the first embodiment.

First, the index reconstructing unit 110B derives luma_log2_weight_denom set in the index information as a predicted value (step S101).

Subsequently, the index reconstructing unit 110B subtracts luma_log2_weight_denom from chroma_log2_weight_denom (step S102) and sets the difference value as delta_chroma_log2_weight_denom in the index information (step S103).

FIG. 15 is a flowchart illustrating an example of chroma_log2_weight_denom restoration processing according to the first embodiment.

First, the index reconstructing unit 110B derives the luma_log2_weight_denom already set in the index information as a predicted value (step S201).

Subsequently, the index reconstructing unit 110B adds luma_log2_weight_denom to delta_chroma_log2_weight_denom (step S202), and sets the added value to the index information as chroma_log2_weight_denom (step S203).

In general, the fade effect is unlikely to change with time in different color spaces, so that the fixed point precision of each signal component has a strong correlation between the luminance component and the color difference component. Therefore, the amount of information indicating the fixed point precision can be reduced by performing the prediction in the color space in this way.

Note that although the luminance component is subtracted from the color difference component in Expression (10), the color difference component may be subtracted from the luminance component. In this case, the equation (11) may be modified according to the equation (10).

Next, a method of predicting luma_weight_lx[i] and chroma_weight_lx[i][j] representing the weighting factors of the luminance and color difference signals 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] increase/decrease 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, the luma_weight_lx[i] is (1<<3) assuming that there is no change in brightness. On the other hand, when the value of luma_log2_weight_denom is 5, the luma_weight_lx[i] is (1<<5) assuming that there is no change in brightness.

Therefore, the index reconstructing unit 110B performs the prediction process using the weighting coefficient when there is no brightness change as the reference coefficient (default value). Specifically, the index reconstructing unit 110B performs the prediction process of luma_weight_lx[i] using Formulas (12) to (13), and performs the restoration process using Formula (14). Similarly, the index reconstructing unit 110B performs the prediction process of chroma_weight_lx[i] using Formulas (15) to (16), and performs the restoration process using Formula (17).

delta_luma_weight_lx[i] = (luma_weight_lx[i]-default_luma_weight_lx) (12)

default_luma_weight_lx = (1<<luma_log2_weight_denom) (13)

luma_weight_lx[i] = (default_luma_weight_lx + delta_luma_weight_lx[i]) (14)

delta_chroma_weight_lx[i][j] = (chroma_weight_lx[i][j]-default_chroma_weight_lx) (15)

default_chroma_weight_lx = (1<<chroma_log2_weight_denom) (16)

chroma_weight_lx[i][j] = (default_chroma_weight_lx + delta_chroma_weight_lx[i][j]) (17)

Here, default_luma_weight_lx and default_chroma_weight_lx are default values with no brightness change in the luminance component and the color difference component, respectively.

FIG. 16 is a flowchart showing an example of a luma_weight_lx[i] prediction process of the first embodiment.

First, the index reconstructing unit 110B derives luma_log2_weight_denom set in the index information (step S301) and calculates default_luma_weight_lx as a predicted value (step S302).

Subsequently, the index reconstructing unit 110B subtracts default_luma_weight_lx from luma_weight_lx[i] (step S303), and sets the difference value in the index information as delta_luma_weight_lx[i] (step S304).

Note that the prediction process can be applied to luma_weight_lx[i] by repeating this process for the number of reference images.

FIG. 17 is a flowchart showing an example of the restoration process of luma_weight_lx[i] according to the first embodiment.

First, the index reconstructing unit 110B derives delta_luma_weight_lx[i] already set in the index information (step S401) and calculates default_luma_weight_lx as a predicted value (step S402).

Subsequently, the index reconstructing unit 110B adds delta_luma_weight_lx[i] to default_luma_weight_lx (step S403), and sets the added value as luma_weight_lx[i] in the index information (step S404).

Although the flowchart for the luminance component is shown here, the prediction process and the restoration process can be similarly realized for the color difference component (chroma_weight_lx[i][j]).

An image including a fade effect is often faded at a specific fade change point, and other images are usually natural images or images without a fade effect. In this case, the weighting factor is often taken when there is no change in brightness. Therefore, it is possible to reduce the code amount of the weighting factor by deriving the initial value when there is no change in brightness from the fixed-point precision and using it as the predicted value.

Note that the prediction values of the weighting factors (luma_weight_lx[i] and chroma_weight_lx[i][j]) of the luminance and color difference signals may be derived with different reference numbers or different POC numbers. In this case, assuming that the reference number closest to the encoding target slice is base_idx, the index reconstruction unit 110B performs the prediction process of luma_weight_lx[i] using Equation (18) and uses Equation (19). , Restore process. Similarly, the index reconstructing unit 110B performs the prediction process of chroma_weight_lx[i][j] using Equation (20) and the restoration process using Equation (21).

delta_luma_weight_lx[i] = (luma_weight_lx[i]-luma_weight_lx[base_idx]) (18)

luma_weight_lx[i] = (delta_luma_weight_lx[i] + luma_weight_lx[base_idx]) (19)

delta_chroma_weight_lx[i][j] = (chroma_weight_lx[i][j]-chroma_weight_lx[base_idx][j]) (20)

chroma_weight_lx[i][j] = (delta_chroma_weight_lx[i][j] + chroma_weight_lx[base_idx][j]) (21)

Here, in the equations (18) and (20), i≠base_idx. Since the weighting coefficient of the reference number indicated by base_idx cannot be used in Expressions (18) and (20), Expressions (12) to (13) and (15) to (16) may be used.

FIG. 18 is a flowchart showing another example of the luma_weight_lx[i] prediction process of the first embodiment.

First, the index reconstructing unit 110B sets baseidx indicating a reference number serving as a reference (step S501). Here, the value of baseidx is assumed to be 0.

Next, the index reconstructing unit 110B derives luma_weight_lx[baseidx] as a predicted value from the index information based on baseidx (step S502). Note that the luma_weight_lx[baseidx] of the index information indicated by baseidx is encoded as a direct value without performing prediction, for example.

Subsequently, the index reconstructing unit 110B subtracts luma_weight_lx[baseidx] from luma_weight_lx[i] (step S503), and sets the difference value as delta_luma_weight_lx[i] in the index information (step S504).

Note that the prediction process can be applied to luma_weight_lx[i] other than baseidx by repeating this process for the number of reference images.

FIG. 19 is a flowchart showing another example of the restoration process of luma_weight_lx[i] according to the first embodiment.

First, the index reconstructing unit 110B sets baseidx indicating a reference number as a reference (step S601). Here, the value of baseidx is assumed to be 0.

Subsequently, the index reconstructing unit 110B derives luma_weight_lx[baseidx] as a predicted value from the index information based on baseidx (step S602). Note that the luma_weight_lx[baseidx] of the index information indicated by baseidx is encoded or decoded as a direct value without performing prediction, for example.

Subsequently, the index reconstructing unit 110B adds delta_luma_weight_lx[i] to luma_weight_lx[baseidx] (step S603), and sets the added value as luma_weight_lx[i] in the index information (step S604).

Although the flowchart for the luminance component is shown here, the prediction process and the restoration process can be similarly realized for the color difference component (chroma_weight_lx[i][j]). In addition, here, the prediction method and the restoration method of the luma_weight_lx[i] are described as an example, but the luma_offset_lx[i] can be similarly predicted and restored.

In addition, the prediction values of the weighting coefficients (luma_weight_lx[i] and chroma_weight_lx[i][j]) of the luminance and color difference signals may be derived using the distance from the reference slice to be encoded. In this case, the index reconstructing unit 110B performs the prediction process of luma_weight_lx[i] by using the formula (22), and performs the restoration process by using the formula (23). Similarly, the index reconstructing unit 110B performs the prediction process of chroma_weight_lx[i][j] using Equation (24) and the restoration process using Equation (25).

delta_luma_weight_lx[i] = (luma_weight_lx[i]-luma_weight_lx[i-1]) (22)

luma_weight_lx[i] = (delta_luma_weight_lx[i] + luma_weight_lx[i-1]) (23)

delta_chroma_weight_lx[i][j] = (chroma_weight_lx[i][j]-chroma_weight_lx[i-1][j]) (24)

chroma_weight_lx[i][j] = (delta_chroma_weight_lx[i][j] + chroma_weight_lx[i-1][j]) (25)

Here, in equations (22) and (24), i≠0.

The prediction process and the decoding process are equivalent to introducing the (i-1)th value (i≠0) in baseidx in the flowcharts of FIGS. 18 and 19, and thus the description thereof will be omitted. Although the flowchart for the luminance component is shown here, the prediction process and the restoration process can be similarly realized for the color difference component (chroma_weight_lx[i][j]). In addition, here, the prediction method and the restoration method of the luma_weight_lx[i] are described as an example, but the luma_offset_lx[i] can be similarly predicted and restored.

As a reference slice that can be referred to by the encoding target slice, a slice that is temporally or spatially close to the encoding target slice is often set from the viewpoint of encoding efficiency. Here, since the changes in luminance of slices that are continuous in terms of time distance have a high correlation, the weight coefficient and the offset also have a high time distance correlation. Therefore, it is possible to efficiently reduce the code amount by predicting the weighting coefficient and the offset value of the reference slice that are temporally different by using the weighting coefficient and the offset value of the reference reference slice. It should be noted that spatially identical reference slices often have the same weighting factor and offset value. Therefore, by introducing prediction for the same reason, the code amount can be reduced.

Next, a method of predicting chroma_offset_lx[i][j] representing the offset of the color difference signal will be described. In the YUV color space, the color difference component represents a color with an amount of deviation from the median value. For this reason, the amount of change from the change in brightness considering the median can be used as the predicted value using the weighting coefficient. Specifically, the index reconstructing unit 110B performs the prediction process of chroma_offset_lx[i][j] using the formulas (26) to (27), and performs the restoration process using the formula (28).

delta_chroma_offset_lx[i][j] = (chroma_offset_lx[i][j] + (( MED * chroma_weight_lx[i][j])>> chroma_log2_weight_denom)-MED) …(26)

MED = (MaxChromaValue>>1) (27)

Here, MaxChromaValue indicates the maximum brightness at which the color difference signal can be obtained. For example, in the case of 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) (28)

FIG. 20 is a flowchart showing an example of chroma_offset_lx[i][j] prediction processing according to the first embodiment.

First, the index reconstructing unit 110B derives chroma_log2_weight_denom set in the index information (step S701).

Subsequently, the index reconstructing unit 110B derives chroma_offset_lx[i][j] set in the index information (step S702).

Subsequently, the index reconstructing unit 110B derives the intermediate value of the maximum value (maximum signal) of the color difference signals (step S703).

Subsequently, the index reconstructing unit 110B derives delta_chroma_offsett_lx[i][j] and sets it as index information (step S704).

21 is a flowchart showing an example of chroma_offset_lx[i][j] restoration processing according to the first embodiment.

First, the index reconstructing unit 110B derives chroma_log2_weight_denom already set in the index information (step S801).

Subsequently, the index reconstructing unit 110B derives chroma_offset_lx[i][j] set in the index information (step S802).

Subsequently, the index reconstructing unit 110B derives the intermediate value of the maximum value (maximum signal) of the color difference signals (step S803).

Subsequently, the index reconstructing unit 110B derives chroma_offsett_lx[i][j] and sets it as index information (step S804).

By using the signal characteristics of the color difference signal and introducing a prediction value that considers the amount of deviation from the median value, the code amount of the offset value of the color difference signal is reduced compared to the case where the offset value is coded as it is. it can.

Next, H.264. A method of deriving a weighted coefficient and a prediction value with fixed-point precision using a WP parameter derivation method of implicit weighted prediction of weighted prediction defined in H.264 and the like will be described. H. In the H.264 implicit weighted prediction, the weighting factor is derived (the offset becomes 0) according to the temporal distance between the reference slices (the time ratio of the POC numbers). For the temporal distance between reference slices, the distance between the encoding target slice and the reference slice is derived based on the POC number, and the weighting factor is determined based on the distance ratio. At this time, the fixed point precision is set to the fixed value 5.

For example, H. In H.264, weighting factors are derived according to the pseudo code shown in equation (29).

td = Clip3(-128, 127, POCA-POCB)
tb = Clip3(-128, 127, POCT-POCA)
tx = (td != 0 )? (( 16384 + abs( td / 2 )) / td ): (0)
DistScaleFactor = Clip3( -1024, 1023, (tb * tx + 32) >> 6)
implicit_luma_weight_l0[i] = 64-(DistScaleFactor >> 2)
implicit_luma_weight_l1[i] = DistScaleFactor >> 2 …(29)

Here, POCA is the POC number of the reference image A corresponding to list 1, POCB is the POC number of the reference image B corresponding to list 0, and POCT is the POC number of the prediction target image. Clip3(L,M,N) is a function that performs clipping processing so that the last argument N does not exceed the range between the minimum value L and the maximum value M indicated by the first two. The abs() function is a function that returns the absolute value of its argument. td and tb represent time ratios, td is the difference between the POC number of the reference image corresponding to list 1 and the POC number of the reference image corresponding to list 0, and tb is the POC number of the prediction target image and the list. The difference between the POC numbers of the reference images corresponding to 0 is shown. These values lead to the scaling variable DistScaleFactor at the distance of the weighting factor. Based on DistScaleFactor, the weighting factors (implicit_luma_weight_l0[i], implicit_luma_weight_l1[i]) corresponding to list 0 and list 1 are derived. The color difference signal is set in the same manner. The index reconstructing unit 110B uses the fixed-point precision implicit_log2_weight_denom derived here to predict the fixed-point precision by the mathematical expression (30).

delta_luma_log2_weight_denom = (luma_log2_weight_denom-implicit_log2_weight_denom) (30)

The fixed point precision of the color difference signal can also be predicted by the mathematical expression (30). This value is restored by equation (31).

luma_log2_weight_denom = (delta_luma_log2_weight_denom + implicit_log2_weight_denom) …(31)

The fixed point precision of the color difference signal can also be restored by the same method as Expression (31).

Next, a weight coefficient prediction formula will be described. When the implicit weighting coefficient is implicit_luma_weight_lx[i], the index reconstructing unit 110B predicts the weighting coefficient luma_weight_lx[i] with Expression (32) and restores it with Expression (33).

if(luma_log2_weight_denom >= implicit_log2_weight_denom) {
norm_denom = (luma_log2_weight_denom-implicit_log2_weight_denom)
delta_luma_weight_lx[i] = (luma_weight_lx[i]-(implicit_luma_weight_lx[i] << norm_denom))
}
else{
norm_denom = (implicit_log2_weight_denom-luma_log2_weight_denom)
delta_luma_weight_lx[i] = (luma_weight_lx[i]-(implicit_luma_weight_lx[i] >> norm_denom))
} (32)

Here, the index reconstructing unit 110B corrects the weighting factor and uses it for prediction depending on whether the fixed-point precision of implicit weighted prediction is larger or smaller.

if(luma_log2_weight_denom >= implicit_log2_weight_denom) {
norm_denom = (luma_log2_weight_denom-implicit_log2_weight_denom)
luma_weight_lx[i] = (delta_luma_weight_lx[i] + (implicit_luma_weight_lx[i] << norm_denom))
}
else{
norm_denom = (implicit_log2_weight_denom-luma_log2_weight_denom)
luma_weight_lx[i] = (delta_luma_weight_lx[i] + (implicit_luma_weight_lx[i] >> norm_denom))
} (33)

In addition, although the example of the weighting coefficient of the luminance component is shown in Expression (32), the prediction value can be derived also for the color difference component by using a similar method.

FIG. 22 is a flowchart showing another example of the luma_weight_lx[i] prediction process of the first embodiment.

First, the index reconstructing unit 110B derives luma_log2_weight_denom set in the index information (step S901).

Subsequently, the index reconstructing unit 110B sends the H.264. According to the H.264 implicit weighted prediction derivation method, implicit_log2_weight_denom and implicit_luma_weight_lx[i] are derived (steps S902 and S903).

Subsequently, the index reconstructing unit 110B determines whether luma_log2_weight_denom is greater than or equal to implicit_log2_weight_denom (step S904).

When luma_log2_weight_denom is greater than or equal to implicit_log2_weight_denom (Yes in step S904), the index reconstructing unit 110B subtracts implicit_log2_weight_denom from luma_log2_weight_denom (step S905) and derives the predicted value by subtracting implicit_luma_weight_lx[i] (left shift). Step S906).

On the other hand, when luma_log2_weight_denom is not greater than or equal to implicit_log2_weight_denom (No in step S904), the index reconstructing unit 110B subtracts luma_log2_weight_denom from implicit_log2_weight_denom (step S907) and derives the predicted value by subtracting implicit_luma_weight_lx[i] and shifting it to the right. Yes (step S908).

Subsequently, the index reconstructing unit 110B subtracts the predicted value derived from luma_weight_lx[i] (step S909), and sets the subtracted value (difference value) in the index information (step S910).

FIG. 23 is a flowchart showing another example of the luma_weight_lx[i] restoration processing according to the first embodiment.

First, the index reconstructing unit 110B derives luma_log2_weight_denom already set in the index information (step S1001).

Subsequently, the index reconstructing unit 110B sends the H.264. According to the derivation method of H.264 implicit weighted prediction, implicit_log2_weight_denom and implicit_luma_weight_lx[i] are derived (steps S1002 and S1003).

Subsequently, the index reconstructing unit 110B determines whether luma_log2_weight_denom is greater than or equal to implicit_log2_weight_denom (step S1004).

When luma_log2_weight_denom is greater than or equal to implicit_log2_weight_denom (Yes in step S1004), the index reconstructing unit 110B subtracts implicit_log2_weight_denom from luma_log2_weight_denom (step S1005), and derives the predicted value by subtracting implicit_luma_weight_lx[i] (left shift). Step S1006).

On the other hand, when luma_log2_weight_denom is not equal to or greater than implicit_log2_weight_denom (No in step S1004), the index reconstructing unit 110B subtracts luma_log2_weight_denom from implicit_log2_weight_denom (step S1007) and derives the predicted value by subtracting implicit_luma_weight_lx[i] and shifting it to the right. Yes (step S1008).

Subsequently, the index reconstructing unit 110B adds the derived prediction value to delta_luma_weight_lx[i] (step S1009), and sets the added value as index information (step S1010).

The plurality of prediction methods described above can be used not only individually but also in combination. For example, by combining Expression (10), Expressions (12) to (13), Expressions (15) to (16), and Expressions (26) to (27), the code amount of the syntax element in the index information is combined. Can be efficiently reduced.

As described above, in the first embodiment, the index setting unit 108 outputs index information obtained by mapping the WP parameter information into the corresponding syntax configuration, and the index reconfiguration unit 110B outputs the redundant representation of the syntax element to the slice. Predict based on information encoded within. Therefore, according to the first embodiment, the code amount can be reduced as compared with the case where the syntax element is encoded as it is (with a direct value).

Here, based on the definition order (encoding order) of the syntax elements used in the slice to be encoded, the predicted value is derived as the intra-frame correlation from the already encoded syntax elements, and the brightness does not change. By deriving the prediction value from the default value assuming that, it is possible to perform prediction that makes use of the characteristics of the syntax element, and as a result, it is possible to reduce the overhead required for encoding the syntax element.

It should be noted that syntax elements not defined in the present embodiment may be inserted between the rows of the syntax table illustrated in FIGS. 10 to 13 of the first embodiment, and description regarding other conditional branches is included. May be. Further, the syntax table may be divided into a plurality of tables or the plurality of syntax tables may be integrated. Moreover, the term of each syntax element illustrated can be arbitrarily changed.

As described above, the encoding device 100 of the first embodiment solves the problem of reduction in encoding efficiency by deleting spatial redundancy using the correlation of parameters of information to be encoded. The encoding apparatus 100 can reduce the code amount as compared with the conventional configuration in which the syntax elements used in the weighted motion compensation prediction are encoded as they are (in direct values).

(Second embodiment)
In the second embodiment, a decoding device that decodes the encoded data encoded by the encoding device of the first embodiment will be described.

FIG. 24 is a block diagram showing an example of the configuration of the decoding device 800 according to the second embodiment.

The decoding device 800 decodes the encoded data accumulated in an input buffer (not shown) or the like into a decoded image and outputs it as an output image to an output buffer (not shown). The encoded data is output from, for example, the encoding device 100 in FIG. 1 or the like, 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. 24, the decoding device 800 includes a decoding unit 801, an inverse quantization unit 802, an inverse orthogonal transformation unit 803, an addition unit 804, a predicted image generation unit 805, and an index setting unit 806. Prepare The inverse quantization unit 802, the inverse orthogonal transformation unit 803, the addition unit 804, and the prediction image generation unit 805 are the inverse quantization unit 104, the inverse orthogonal transformation unit 105, the addition unit 106, the prediction image generation unit 107, and the prediction image generation unit 107 of FIG. 1, respectively. Is substantially the same as or similar to the element. The decoding control unit 807 shown in FIG. 24 controls the decoding device 800 and can be realized by, for example, a CPU.

The decoding unit 801 decodes each frame or field based on the syntax for decoding the encoded data. The decoding unit 801 includes an entropy decoding unit 801A and an index reconstructing unit 801B.

The entropy decoding unit 801A sequentially entropy-decodes the code string of each syntax to obtain motion information including a prediction mode, motion vector, reference number, and the like, index information for weighted motion compensation prediction, quantized transform coefficient, and the like. The coding parameters of the coding target block are reproduced. Here, the coding parameters are all parameters other than those described above that are necessary for decoding information regarding transform coefficients, information regarding quantization, and the like.

Specifically, the entropy decoding unit 801A has a function of performing a decoding process such as a variable length decoding process or an arithmetic decoding process on the input coded data. For example, H.264. In H.264, context-based variable-length coding (CAVLC) and context-based arithmetic coding (CABAC) are used for context-based adaptive coding (CABAC). These processes are also called decryption processes.

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

The decoding unit 801 outputs the motion information, the index information, and the quantized transform coefficient, inputs the quantized transform coefficient to the inverse quantization unit 802, inputs the index information to the index setting unit 806, and sets the motion information to the predicted image. Input to the generation unit 805.

The inverse quantization unit 802 performs an inverse quantization process on the quantized transform coefficient input from the decoding unit 801, and obtains a restored transform 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 quantized transform coefficient by the quantized step size derived from the quantized information to obtain the restored transformed coefficient. The inverse quantization unit 802 outputs the restoration transform coefficient and inputs it to the inverse orthogonal transform unit 803.

The inverse orthogonal transform unit 803 performs an inverse orthogonal transform corresponding to the orthogonal transform performed on the encoding side on the restored transform coefficient input from the inverse quantization unit 802 to obtain a restored prediction error. The inverse orthogonal transformation 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 transformation unit 803 and the corresponding prediction image to generate a decoded image. The addition unit 804 outputs the decoded image and inputs the decoded image to the predicted 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 (not shown) or the like, and is output to a display device system such as a display or monitor (not shown) or a video device system in accordance with the output timing managed by the decoding control unit 807, for example. Is output.

The index setting unit 806 receives the index information input from the decoding unit 801, converts the index information into WP parameter information, outputs the WP parameter information, and inputs the WP parameter information to the predicted image generation unit 805. Specifically, the index setting unit 806 receives the index information decoded by the entropy decoding unit 801A and reconstructed by the index reconstructing unit 801B. Then, the index setting unit 806 confirms the list of reference images and the reference numbers, converts them into WP parameter information, and outputs the converted WP parameter information to the predicted image generation unit 805. The WP parameter information has already been described with reference to FIGS. 8A and 8B, and thus the description will be omitted.

The predicted image generation unit 805 generates a predicted image 815 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 predicted image generation unit 805 will be described with reference to FIG. Like the predicted image generation unit 107, the predicted image generation unit 805 includes a multiple 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 decoded image input from the addition unit 106 as a 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≧2) for temporarily holding a reference image.

The prediction parameter control unit 204 prepares a plurality of combinations of reference image numbers and prediction parameters as a table based on the motion information input from the decoding unit 801. Here, the motion information refers to a motion vector used for motion compensation prediction, a reference image number, information about 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 used for generating the predicted image and the prediction parameter based on the motion information, inputs the reference image number to the reference image selector 205, and outputs the prediction parameter. Is input to the unidirectional motion compensation unit 203.

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

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

The unidirectional predictive motion compensation unit 203 outputs the unidirectional predicted 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 unidirectionally predicted images, so the unidirectionally predicted motion compensation unit 203. Stores the unidirectional predicted image corresponding to the first in the memory 202, and directly outputs the unidirectional predicted image corresponding to the second to the multi-frame motion compensation unit 201. Here, the unidirectionally predicted image corresponding to the first is the first predicted image, and the unidirectionally predicted image corresponding to the second is the second predicted image.

It should be noted that two unidirectional motion compensation units 203 may be prepared and each may generate two unidirectional predicted images. In this case, if the motion information (prediction parameter) indicates unidirectional prediction, the unidirectional motion compensating unit 203 may directly output the first unidirectional predicted image as the first predicted image to the multi-frame motion compensating 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 prediction motion compensation unit 203, and the WP parameter information input from the motion evaluation unit 109. , Weighted prediction is performed to generate a predicted image. The multi-frame motion compensation unit 201 outputs the predicted image and inputs it to the addition unit 804.

Here, the details of the multi-frame motion compensation unit 201 will be described with reference to FIG. 6. 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. It is input to the motion compensation unit 302.

Here, the WP parameter information includes the fixed point precision of the weighting factor, the first WP application flag corresponding to the first prediction image, the first weighting factor, and the first offset, and the second WP adaptation corresponding to the second prediction image. It includes information on a flag, a second weighting factor, and a second offset. The WP application flag is a parameter that can be set for each corresponding reference image and signal component, and indicates whether to perform weighted motion compensation prediction. The weight information includes fixed-point precision of the weight coefficient, first weight coefficient, first offset, second weight coefficient, and second offset information. The WP parameter information represents the same information as in the first embodiment.

Specifically, when the WP parameter information is input from the index setting unit 806, the WP parameter control unit 303 separates the WP parameter information into a first WP applicable flag, a second WP applicable flag, and weight information, and outputs it. , 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.

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. When each WP application flag is 0, the WP selectors 304 and 305 connect each output terminal to the default motion compensation unit 301. 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 the respective output ends to the weighted motion compensation unit 302 when the 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 unidirectionally predicted images (first predicted image and second predicted image) input from the WP selectors 304 and 305, and generates a predicted image. Specifically, when the first WP application flag and the second WP application flag are 0, the default motion compensation unit 301 performs the average value process based on Expression (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 calculate the final prediction image based on Expression (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. Performs 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 the weighting process based on Expression (7).

Note that the weighted motion compensation unit 302 controls the logWDC, which is fixed-point precision, as in Equation (8) when the first prediction image and the second prediction image have different calculation precisions from each other, thereby performing a rounding process. To realize.

In addition, 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 Expression (9). To calculate.

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

Since the fixed point precision of the weighting factor has already been described with reference to FIG. 7, the description thereof will be omitted. Note that, in the case of unidirectional prediction, various parameters (second WP adaptation flag, second weighting coefficient, and second offset information) corresponding to the second predicted image are not used, so set to a predetermined initial value. It may have been done.

The decoding unit 801 uses the syntax 500 shown in FIG. The syntax 500 shows the structure of the encoded data to be decoded by the decoding unit 801. The syntax 500 has already been described with reference to FIG. 9, so description thereof will be omitted. Also, the picture parameter set syntax 505 has already been described with reference to FIG. 10 except that the encoding is decoding, and therefore description thereof will be omitted. Further, the slice header syntax 507 has also been described with reference to FIG. 11 except that the encoding is decoding, and thus the description thereof will be omitted. Further, the description of the pread weight table syntax 508 has also been omitted because it has already been described with reference to FIG. 12 except that the encoding is decoding.

Here, the details of the method of predicting 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 reconstructing unit 801B. The syntax configuration explicitly showing the prediction method of the second embodiment is the same as that of the second embodiment and is as shown in FIG.

Regarding the prediction method between the signals of luma_log2_weight_denom and chroma_log2_weight_denom indicating the fixed point precision of the weighting factor, the restoration process is performed using Expression (11). Details of the restoration process are as shown in FIG.

As for the method of predicting luma_weight_lx[i] and chroma_weight_lx[i][j], which represent the weighting factors of the luminance and color difference signals, the restoration process is performed using Equations (14) and (17). Details of the restoration process are as shown in FIG.

For the prediction method of deriving the prediction values of the weighting factors (luma_weight_lx[i] and chroma_weight_lx[i][j]) of the luminance and color difference signals with different reference numbers or different POC numbers, formulas (19) and (21) are used. Restoration processing is performed using this. Details of the restoration process are as shown in FIG.

For the prediction method for deriving the prediction values of the weighting factors (luma_weight_lx[i] and chroma_weight_lx[i][j]) of the luminance and chrominance signals using the distance from the reference slice to be encoded, Equation (23) and The restoration process is performed using (25). The details of the restoration process are equivalent to introducing the (i-1)th value (i≠0) into baseidx in the flowchart of FIG.

H. For the weight coefficient and the fixed-point-precision prediction value derivation method using the WP parameter derivation method of the implicit weighted prediction of the weighted prediction defined in H.264 or the like, using Equations (31) and (33), Restoration processing is performed. Details of the restoration process are as shown in FIG.

The plurality of prediction methods described above can be used not only individually but also in combination. For example, by combining Expression (11), Expression (14), Expression (17), and Expression (28), 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 decoding device 800 eliminates the problem of reduced coding efficiency by deleting the spatial redundancy by using the correlation of the parameters of the information to be coded. The decoding device 800 can reduce the code amount as compared with the conventional configuration in which the syntax elements used in the weighted motion compensation prediction are encoded as they are (in direct values).

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

The first to second embodiments have been described by exemplifying the prediction target block size such as the 4×4 pixel block, the 8×8 pixel block, and the 16×16 pixel block, 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 code amount 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 division information and the locally decoded image or the quality of the decoded image.

In the above-described first and second embodiments, for simplification, a comprehensive description is given regarding the color signal component without distinguishing between the luminance signal and the prediction processing in the color difference signal. However, if the prediction process differs between the luminance signal and the color difference signal, the same or different prediction method may be used. If different prediction methods are used between the luminance signal and the color difference signal, the selected prediction method for the color difference signal can be encoded or decoded in the same manner as the luminance signal.

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

In the first and second embodiments described above, syntax elements not defined in the present embodiment can be inserted between the rows of the table shown in the syntax configuration, and a description regarding other conditional branching is included. It doesn't matter. 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, each of the embodiments realizes highly efficient weighted motion compensation prediction processing while solving the problem of encoding redundant information of syntax configuration when performing weighted motion compensation prediction. Therefore, according to each embodiment, the coding efficiency is improved and the subjective image quality is also improved.

While 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 forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and the gist of the invention, and are also included in the invention described in the claims and the scope equivalent thereto.

For example, it is possible to store the program that implements the processes of the above-described embodiments in a computer-readable storage medium and provide the program. The storage medium may be a magnetic disk, an optical disk (CD-ROM, CD-R, DVD, etc.), a magneto-optical disk (MO, etc.), a semiconductor memory, or any other computer-readable storage medium that can store a program. For example, the storage format may be any form.

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

100 Encoding device 101 Subtraction unit 102 Orthogonal transformation unit 103 Quantization unit 104 Inverse quantization unit 105 Inverse orthogonal transformation unit 106 Addition unit 107 Predicted image generation unit 108 Index setting unit 109 Motion evaluation unit 110 Encoding unit 110A Entropy encoding unit 110B Index reconstruction unit 111 Encoding control unit 201 Multi-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 reconstruction unit 802 Dequantization unit 803 Inverse orthogonal transformation unit 804 Addition unit 805 Predicted image generation unit 806 Index setting unit 807 Decryption control unit

Claims (2)

Setting indexes for a reference image, a luminance weighting factor, a first fixed-point precision of the luminance weighting factor, a color difference weighting factor, and a second fixed-point precision of the color difference weighting factor;
Encoding either the first fixed point precision or the second fixed point precision;
Encoding a first difference value that is the same as the difference between the first fixed point precision and the second fixed point precision;
The value is the same as the value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision, and the pixel value change in luminance between the reference image and the target image is specific. Deriving, based on the first fixed point precision, a first reference value that is the same value as the value of the weighting coefficient of the brightness when the value is equal to or less than the reference.
Encoding a second difference value of the luminance weighting coefficient, which is the same value as the difference between the first reference value and the luminance weighting coefficient;
The value is the same as the value obtained by left-shifting "1" by the number of bits determined by the second fixed-point precision, and the pixel value change between the reference image and the target image is less than or equal to a specific criterion. A second reference value having the same value as the value of the color difference weighting coefficient in the case of
Encoding a third difference value that is the same value as the difference between the color difference weighting factor and the second reference value;
An encoding method including. Decoding a first fixed point precision of the luminance weighting factor;
Decoding a first difference value that is the same as the difference between the first fixed-point precision and the second fixed-point precision of the color difference weighting factor;
Determining the second fixed-point precision by adding the first fixed-point precision and the first difference value;
The value is the same as the value obtained by left-shifting "1" by the number of bits determined by the first fixed-point precision, and the pixel value change in luminance between the reference image and the target image is a specific criterion. the same value as the value of the weighting factor of the luminance when the following determining a first reference value of the weighting factor of the luminance,
Decoding a second difference value of the luminance weighting coefficient, which is the same value as the difference between the luminance weighting coefficient and the first reference value;
Determining the weighting coefficient of the luminance by adding the first reference value and the second difference value;
The value is the same as the value obtained by left-shifting “1” by the number of bits determined by the second fixed-point precision, and the weighting coefficient of the color difference and between the reference image and the target image are Decoding a third difference value that is a difference between a second reference value that is the same value as the value of the color difference weighting coefficient when the pixel value change is less than or equal to a specific reference,
Deriving the second reference value based on the second fixed point precision;
Deriving the weighting coefficient of the color difference by adding the third difference value and the second reference value;
Decoding method including.