JP2017121070A - Electronic equipment, decoding method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide electronic equipment, a decoding method, and a program that can enhance the encoding efficiency.SOLUTION: A processor of electronic equipment decodes a first fixed point precision of a weighting coefficient of luminance, decodes a first difference value corresponding to the difference between the first fixed point precision and a second fixed point precision of a weighting coefficient of color difference, determines the second fixed point precision by adding the first fixed point precision and the first difference value, determines, as the first reference value of the weighting coefficient of luminance, a value obtained by shifting "1" to the left by only the number of bits determined by the first fixed point precision, decodes the second difference value of the weighting coefficient of luminance corresponding to the difference between the weighting coefficient of luminance and the first reference value, determines the weighting coefficient of luminance by adding the first reference value and the second difference value, determines, the second reference value of the weighting coefficient of color difference, a value obtained by shifting "1" to the left by only the number of bits determined by the second fixed point precision, decodes a third difference value of the weighting coefficient of color difference corresponding to the difference between the weighting coefficient of color difference and the second reference value, and adds the second reference value and the third difference value to determine the weighting coefficient of color difference.SELECTED DRAWING: Figure 1

Description

  Embodiments described herein relate generally to an electronic device, a decoding method, and a program.

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

  H. H.264 discloses an inter-prediction coding scheme that eliminates temporal redundancy and realizes high coding efficiency by performing fractional accuracy motion compensated prediction using a coded image as a reference image. ing.

  Also, a scheme for encoding moving images including fade and dissolve effects with higher efficiency than the inter prediction encoding schemes 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 brightness in the time direction, fractional accuracy motion compensation prediction is performed on an input moving image having luminance and two color differences. Then, the prediction image is multiplied by the weighting factor using an index indicating a combination including the reference image, the weighting factor for each luminance and two color differences, and the offset for each luminance and two color differences, and the offset is added.

JP 2004-7377 A

  However, in the conventional technique as described above, since the index is encoded with the direct value, the encoding efficiency is lowered. The problem to be solved by the present invention is to provide an electronic device, a decoding method, and a program that can improve encoding efficiency.

  The electronic device according to the embodiment is an electronic device to which encoded data is input, and includes a processing unit. The processing unit decodes the first fixed-point precision of the luminance weight coefficient from the encoded data, and determines the first fixed-point precision and the second fixed-point precision of the color difference weight coefficient from the encoded data. The second fixed-point precision is determined by decoding the first difference value, which is the same value as the difference, and adding the first fixed-point precision and the first difference value, and the first fixed-point precision The same value as the value obtained by left-shifting “1” by the number of bits determined by accuracy is determined as the first reference value of the luminance weighting coefficient, and the luminance weighting coefficient is determined from the encoded data. Decoding a second difference value of the luminance weighting coefficient that is the same value as the difference from the first reference value, and adding the first reference value and the second difference value to thereby add the luminance weighting coefficient Determined by the second fixed-point precision. A second reference value of the color difference weighting coefficient is determined based on a value obtained by left-shifting “1” by the number of bits, and the color difference weighting coefficient and the second reference value are determined from the encoded data. The color difference weighting coefficient is determined by decoding the third difference value of the color difference weighting coefficient, which is the same value as the difference, and adding the second reference value and the third difference value.

The block diagram which shows the example of the encoding apparatus of 1st Embodiment. Explanatory drawing which shows the example of the prediction encoding order of the pixel block in 1st Embodiment. The figure which shows the block size example of the coding tree block in 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The figure which shows the specific example of the coding tree block of 1st Embodiment. The block diagram which shows the example of the estimated image generation part of 1st Embodiment. The figure which shows the example of the relationship of the motion vector of the motion compensation prediction in the bidirectional | two-way 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 WP parameter information example of 1st Embodiment. The figure which shows the WP parameter information example 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 tread 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 example of a prediction process of the fixed point precision of 1st Embodiment. 6 is a flowchart illustrating an example of fixed point precision restoration processing according to the first embodiment. The flowchart which shows the example of the prediction process of the weighting coefficient of 1st Embodiment. 6 is a flowchart showing an example of weight coefficient restoration processing according to the first embodiment. 7 is a flowchart illustrating another example of weight coefficient prediction processing according to the first embodiment. 7 is a flowchart illustrating another example of the weighting factor restoration process according to the first embodiment. 5 is a flowchart illustrating an example of color difference signal prediction processing according to the first embodiment. 5 is a flowchart illustrating an example of color difference signal restoration processing according to the first embodiment. 9 is a flowchart illustrating another example of weighting factor prediction processing according to the first embodiment. 12 is a flowchart illustrating another example of the weighting factor restoration process according to 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 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 software by causing a computer to execute a program. In the following description, the term “image” can be appropriately replaced with a term such as “video”, “pixel”, “image signal”, “picture”, or “image data”.

(First embodiment)
In the first embodiment, an encoding apparatus that encodes a moving image will be described.

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

  The encoding apparatus 100 divides each frame or each field constituting the input image into a plurality of pixel blocks, and uses the encoding parameters input from the encoding control unit 111 to predict the encoded code for the divided pixel blocks. To generate a predicted image. The encoding apparatus 100 subtracts the input image divided into a plurality of pixel blocks and the prediction image to generate a prediction error, orthogonally transforms and quantizes the generated prediction error, and further performs entropy encoding to perform encoding. Generate and output data.

  The encoding apparatus 100 performs predictive encoding by selectively applying a plurality of prediction modes in which at least one of the block size of the pixel block and the prediction image generation method is different. The generation method of the prediction image is 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 reference frames that are temporally different. Note that intra prediction is also referred to as intra prediction or intra frame prediction, and inter prediction is also referred to as inter prediction, inter frame prediction, motion compensation prediction, or the like.

  FIG. 2 is an explanatory diagram illustrating 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 predictive encoding from the upper left to the lower right of the pixel block, and the left side of the encoding target pixel block c in the encoding target frame f and The encoded pixel block p is located on the upper side. Hereinafter, for simplification of description, the encoding apparatus 100 performs predictive encoding in the order shown in FIG. 2, but the order of predictive encoding is not limited to this.

  The pixel block represents a unit for processing an image, and corresponds to, for example, an M × N size block (M and N are natural numbers), a coding tree block, a macro block, a sub block, or one pixel. In the following description, the pixel block is basically used in the meaning of the coding tree block, but may be used in other meanings. For example, in the description of the prediction unit, a pixel block is used to mean a pixel block of the prediction unit. 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 illustrating an example of a block size of a coding tree block according to 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 it 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 may not be a square, and may be, for example, an M × N size (M ≠ N) pixel block.

  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 the reference coding tree block. 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.

  The coding tree block can be further divided into quadtrees within one quadtree number. Thereby, a coding tree block can be divided | segmented hierarchically. In this case, the depth of division is defined by Depth. FIG. 3D shows one of the coding tree blocks obtained by dividing the coding tree block of FIG. 3B into quadtrees, and the block size is 32 × 32 (N = 16). The Depth of the coding tree block shown in FIG. 3B is 0, and the Depth of the coding tree block shown in FIG. 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 the raster scan order.

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

  As illustrated 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 The image generation unit 107, the index setting unit 108, the motion evaluation unit 109, and the encoding unit 110 are provided. Note that the encoding control unit 111 illustrated in FIG. 1 controls the encoding apparatus 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 a prediction error and inputs it to the orthogonal transform unit 102.

  The orthogonal transform unit 102 performs orthogonal transform such as discrete cosine transform (DCT) or discrete sine transform (DST) on the prediction error input from the subtraction unit 101 to obtain transform coefficients. The orthogonal transform unit 102 outputs transform coefficients and inputs them 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 or a quantization matrix specified 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 a 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 inverse quantization unit 104 multiplies the quantization transform coefficient by the quantization step size derived from the quantization information to obtain a restored transform coefficient. Note that 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 restored transform coefficient and inputs it to the inverse orthogonal transform unit 105.

  The inverse orthogonal transform unit 105 performs inverse orthogonal transform such as inverse discrete cosine transform (IDCT) or inverse discrete sine transform (IDST) on the restored transform coefficient input from the inverse quantization unit 104, Get the restoration prediction error. Note that 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 reconstruction prediction error and inputs it to the addition unit 106.

  The adding unit 106 adds the restored prediction error input from the inverse orthogonal transform unit 105 and the corresponding predicted image to generate a locally decoded image. The adding unit 106 outputs the local 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 as a reference image in a memory (not shown in FIG. 1), outputs the reference image stored in the memory, and inputs the reference image to the motion evaluation unit 109. . Further, the predicted image generation unit 107 performs weighted motion compensation prediction based on the motion information and WP parameter information input from the motion evaluation unit 109, and generates a predicted image. The predicted image generation unit 107 outputs a predicted image and inputs it to the subtracting unit 101 and the adding unit 106.

  FIG. 4 is a block diagram illustrating an example of the configuration of the predicted image generation unit 107 of the first embodiment. As shown in FIG. 4, the predicted image generation unit 107 includes a multi-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 storing reference images.

  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 indicates a motion vector indicating a shift amount of motion used in motion compensation prediction, a reference image number, information on a prediction mode such as unidirectional / bidirectional prediction, and the like. The prediction parameter refers to information regarding a motion vector and a prediction mode. Then, the prediction parameter control unit 204 selects and outputs a combination of the reference image number and the prediction parameter used for generating the prediction image based on the input image, inputs the reference image number to the reference image selector 205, and outputs the prediction parameter. Is input to the unidirectional motion compensation unit 203.

  The reference image selector 205 is a switch for switching which output terminal 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, if the reference image number is 0, the reference image selector 205 connects the output end of FM1 to the output end of the reference image selector 205. If the reference image number is N-1, the reference image selector 205 refers to the output end of the FMN. Connected to the output terminal of the image selector 205. The reference image selector 205 outputs the reference image stored in the frame memory to which the output terminal 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. Enter.

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

  FIG. 5 is a diagram illustrating an example of a motion vector relationship of motion compensation prediction in bidirectional prediction according to the first embodiment. In motion compensated prediction, interpolation processing is performed using a reference image, and a unidirectional prediction image is generated based on the amount of motion deviation from the pixel block at the encoding target position between the generated interpolation image and the input image. . Here, the amount of deviation is a motion vector. As shown in FIG. 5, in a bi-directional prediction slice (B-slice), a prediction image is generated using a set of two types of reference images and motion vectors. As the interpolation process, an interpolation process with 1/2 pixel accuracy, an interpolation process with 1/4 pixel accuracy, or the like is used, and the value of the interpolation image is generated by performing the filtering process on the reference image. For example, H.P. capable of performing interpolation processing up to 1/4 pixel accuracy on a luminance signal. In H.264, the shift amount is expressed by four times the integer pixel accuracy.

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

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

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

  FIG. 6 is a block diagram illustrating an example of the configuration of the multi-frame motion compensation unit 201 according to 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 a WP application flag and weight information based on the WP parameter information input from the motion evaluation unit 109, inputs the WP application flag to the WP selectors 304 and 305, and weights the weight information. Input to the motion compensation unit 302.

  Here, the WP parameter information includes the fixed-point precision of the weighting factor, the first WP application flag corresponding to the first predicted image, the first weighting factor, the first offset, and the second WP adaptation corresponding to the second predicted image. Contains information on flag, second weighting factor, and 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 information on the fixed point precision of the weight coefficient, the first weight coefficient, the first offset, the second weight coefficient, and the second offset.

  Specifically, when 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 them. 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, when each WP application flag is 1, the WP selectors 304 and 305 connect each output terminal to the weighted motion compensation unit 302. 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 an average value process based on the two unidirectional predicted images (first predicted image and second predicted image) input from the WP selectors 304 and 305 to generate 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 average value processing 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 accuracy of the prediction image is L and the bit accuracy of the first prediction image and the second prediction image is M (L ≦ M), shift2 is formulated by Equation (2), and offset2 is formulated by Equation (3). Is done.

  shift2 = (ML + 1) (2)

  offset2 = (1 << (shift2-1) (3)

  For example, when the bit accuracy of the predicted image is 8 and the bit accuracy of the first predicted image and the second predicted image is 14, 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 and calculates a 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 prediction image (first prediction image), and X is an identifier indicating either 0 or 1 in the reference list. For example, when the reference list is 0, PL0 [x, y] is obtained, and when the reference list is 1, PL1 [x, y] is obtained. offset1 and shift1 are parameters of the rounding process, and are determined by the internal calculation accuracy of the first predicted image. When the bit accuracy of the predicted image is L and the bit accuracy 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 accuracy of the predicted image is 8 and the bit accuracy of the first predicted image is 14, shift1 = 6 from Equation (5) and offset1 = (1 << 5) from Equation (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 factor corresponding to the first predicted image, w1C represents a weighting factor corresponding to the second predicted image, o0C represents an offset corresponding to the first predicted image, and o1C represents an offset corresponding to the second predicted image. . Hereinafter, these are referred to as a first weighting factor, a second weighting factor, a first offset, and a second offset, respectively. 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 spatial 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 performs rounding processing by controlling logWDC, which is fixed-point precision, as in Expression (8) when the calculation accuracy of the first predicted image, the second predicted image, and the predicted image is different. Is realized.

  logWD'C = logWDC + offset1 (8)

  The rounding process can be realized by replacing logWDC in Expression (7) with logWD′C in Expression (8). For example, when the bit accuracy of the predicted image is 8 and the bit accuracy of the first predicted image and the second predicted image is 14, by resetting logWDC, the calculation accuracy similar to shift2 in Equation (1) can be obtained. A batch rounding process can be realized.

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

  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 factor corresponding to unidirectional prediction, and X indicates either 0 or 1 in the reference list. It is an identifier to indicate. For example, when the reference list is 0, PL0 [x, y] and w0C are obtained, and when the reference list is 1, PL1 [x, y] and w1C are obtained.

  Note that the weighted motion compensation unit 302, when the calculation accuracy of the first prediction image, the second prediction image, and the prediction image is different, uses the log WDC, which is a fixed-point accuracy, as in Expression (8) as in the bidirectional prediction. Rounding processing is realized by controlling to.

  The rounding process can be realized by replacing logWDC in Expression (7) with logWD′C in Expression (8). For example, when the bit accuracy of the predicted image is 8 and the bit accuracy of the first predicted image is 14, the round rounding process with the same calculation accuracy as that of shift1 of Expression (4) is realized by resetting logWDC It becomes possible to do.

  FIG. 7 is an explanatory diagram of an example of the fixed-point precision of the weighting coefficient in the first embodiment, and is a diagram illustrating an example of a change between 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 Frame (t), the previous frame in time is Frame (t−1), and the next frame in time is Frame (t + 1). As shown in FIG. 7, in a fade image that changes from white to black, the brightness (gradation value) of the image decreases with time. The weighting coefficient means the degree of change in FIG. 7 and takes a value of 1.0 when there is no change in brightness, as is clear from Equation (7) and Equation (9). The fixed-point precision is a parameter for controlling the step size corresponding to the decimal point of the weighting coefficient, and the weighting coefficient when there is no change in brightness is 1 << logWDC.

  In the case of unidirectional prediction, various parameters (second WP adaptive flag, second weighting factor, and second offset information) corresponding to the second predicted image are not used, and are set to predetermined initial values. May be.

  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 stores 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.

  For example, the motion evaluation unit 109 calculates an error by calculating a difference value starting from a plurality of reference images corresponding to the same position as the input image of the prediction target pixel block, shifts the position with a fractional accuracy, and minimizes the error. Optimal motion information is calculated by a technique such as block matching for searching for a block. In the case of bidirectional prediction, the motion evaluation unit 109 performs block matching including default motion compensation prediction as shown in Equation (1) and Equation (4) using motion information derived by unidirectional prediction. Thus, motion information for bidirectional prediction is calculated.

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

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

  The fixed-point precision of the weighting coefficient is information indicating the precision of the slope, 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 coefficient between Frame (t-1) and Frame (t + 1) is 0.75 in decimal point precision, 3/4 can be expressed with 1/4 precision. The unit 109 sets the fixed point precision to 2 (1 << 2). Since the value of the fixed-point precision affects the code amount when the weighting coefficient is encoded, an optimal value may be selected in consideration of the code amount and the prediction accuracy. Note that the fixed-point precision value may be a predetermined fixed value.

  Further, when the inclinations do not match, the motion evaluation unit 109 can calculate the offset value by obtaining a correction value (deviation amount) corresponding to the intercept of the linear function. For example, in FIG. 7, when the weighting coefficient 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 coefficient is 1 (That is, it corresponds to the decimal point precision 0.50 of the weighting coefficient) is set. In this case, since the decimal point accuracy of the weighting coefficient is deviated from 0.60, which is the optimum value, by 0.10, the motion evaluation unit 109 calculates the correction value for this amount from the maximum value of the pixel and uses it as an offset value. Set. When the maximum value of the pixel is 255, the motion evaluation unit 109 may set a value such as 25 (255 × 0.1).

  In the first embodiment, the motion evaluation unit 109 is illustrated as a function of the encoding device 100. However, the motion evaluation unit 109 is not an essential component of the encoding device 100. For example, the motion evaluation unit 109 is encoded. It is good also as an apparatus outside the converter 100. In this case, the motion information and 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, checks the reference list (list number) and the reference image (reference number), outputs the index information, and outputs the index information to the encoding unit 110. input. The index setting unit 108 generates index information by mapping the WP parameter information input from the motion evaluation unit 109 to syntax elements described later.

  8A and 8B are diagrams illustrating examples of WP parameter information according to the first embodiment. An example of WP parameter information at the time of P-slice is as shown in FIG. 8A, and an example of WP parameter information at the time of B-slice is as shown in FIGS. 8A and 8B. The list number is an identifier indicating the prediction direction, and takes a value of 0 when unidirectional prediction is used, and two values of 0 and 1 can be used when bidirectional prediction is used. The reference numbers are values corresponding to 1 to N indicated in the frame memory 206. Since the WP parameter information is held for each reference list and reference image, the information necessary for the B-slice is 2N when the number of reference images is N.

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

  The encoding parameter is a parameter required for decoding, such as prediction information indicating a prediction method, information on quantization transform coefficients, information on quantization, and the like. For example, the encoding control unit 111 has an internal memory (not shown), the encoding parameters are held in the internal memory, and the encoding parameters of the adjacent already encoded pixel block are used when encoding the pixel block. You can For example, H.M. In the 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, multiplexed with various information such as a multiplexing unit (not shown) and temporarily stored in an output buffer (not shown). (Storage medium) or transmission system (communication line).

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

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

  In order to reduce the code length of the syntax element of the index information input from the index setting unit 108, the index reconstruction unit 110B performs a prediction process according to the characteristics of the parameter of the syntax element, and uses the value of the syntax element as it is (directly). Value) and the difference between the predicted values and output to the entropy encoding unit 110A. A specific example of the prediction process will be described later.

  FIG. 9 is a diagram illustrating an example of the syntax 500 used by the encoding device 100 according to the first embodiment. A syntax 500 indicates a structure of encoded data generated by the encoding apparatus 100 by encoding an input image (moving image data). When decoding the encoded data, a decoding device described later refers to the same syntax structure as that of the syntax 500 and interprets the syntax 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 a field. The slice level syntax 502 includes information necessary for decoding each slice. The coding tree level syntax 503 includes information necessary for decoding each coding tree (ie, each coding tree block). Each of these parts includes more detailed syntax.

  The high level syntax 501 includes sequence and picture level syntaxes such as a sequence parameter set syntax 504, a picture parameter set syntax 505, and an adaptation parameter set syntax 506.

  The slice level syntax 502 includes a slice header syntax 507, a breadweight table syntax 508, a slice data syntax 509, and the like. The tread 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 with a quadtree. The coding tree unit syntax 510 includes a transform unit syntax 511. The transform unit syntax 511 is called in each coding tree unit syntax 510 at the extreme end of the quadtree. The transform unit syntax 511 describes information related to inverse orthogonal transformation and quantization. In these syntaxes, information related to weighted motion compensation prediction may be described.

  FIG. 10 is a diagram illustrating an example of the picture parameter set syntax 505 according to the first embodiment. The weighted_pred_flag is a syntax element indicating, for example, whether the weighted compensated prediction of the first embodiment related to P-slice is valid or invalid. When weighted_pred_flag is 0, the weighted motion compensation prediction of the first embodiment in the P-slice is invalid. Accordingly, the WP application flag included in the WP parameter information is always set to 0, and the WP selectors 304 and 305 connect the respective output terminals 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 the P-slice is valid.

  As another example, when weighted_pred_flag is 1, in the syntax of lower layers (slice header, coding tree block, transform unit, prediction unit, etc.) The validity or invalidity of the weighted motion compensated prediction of one embodiment may be specified.

  For example, weighted_bipred_idc is a syntax element indicating whether the weighted compensated prediction of the first embodiment related to B-slice is valid or invalid. When weighted_bipred_idc is 0, the weighted motion compensated prediction of the first embodiment in the B-slice is invalid. Accordingly, the WP application flag included in the WP parameter information is always set to 0, and the WP selectors 304 and 305 connect the respective output terminals to the default motion compensation unit 301. On the other hand, when weighted_bipred_idc is 1, the weighted motion compensated prediction of the first embodiment in the B-slice is valid.

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

  FIG. 11 is a diagram illustrating an example of the slice header syntax 507 according to the first embodiment. slice_type indicates the slice type (I-slice, P-slice, B-slice, etc.) of the slice. pic_parameter_set_id is an identifier indicating which picture parameter set syntax 505 is to be referred to. num_ref_idx_active_override_flag is a flag indicating whether 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 predicate weight table syntax used for weighted motion compensation prediction. When the above weighted_pred_flag is 1 and P-slice, and when weighted_bipred_idc is 1 and B-slice, this function is Called.

  FIG. 12 is a diagram illustrating an example of the tread 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 the log WDC in Equation (7) or Equation (9). chroma_log2_weight_denom represents the fixed-point precision of the weight coefficient of the color difference signal in the slice, and is a value corresponding to the log WDC in Equation (7) or Equation (9). chroma_format_idc is an identifier representing a color space, and MONO_IDX is a value indicating a monochrome video. 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 signals corresponding to List 0 and List 1, respectively. When this flag is 1, the weighted motion compensated prediction of the luminance signal of the first embodiment is effective over the entire slice. chroma_weight_l0_flag and chroma_weight_l1_flag indicate 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 chrominance signal of the first embodiment is effective over the entire slice. luma_weight_l0 [i] and luma_weight_l1 [i] are the weight coefficients of the i-th corresponding luminance signal managed in list 0 and list 1, respectively. luma_offset_l0 [i] and luma_offset_l1 [i] are offsets of the i-th corresponding luminance signal managed in list 0 and list 1, respectively. These are values corresponding to w0C, w1C, o0C, and o1C, respectively, of Equation (7) or Equation (9). However, C = Y.

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

  Here, the detail of the prediction method of each syntax element relevant to the weighted prediction in a syntax structure is demonstrated. The prediction of syntax elements is performed by the index reconstruction unit 110B. FIG. 13 is a diagram illustrating an example of a syntax configuration that explicitly indicates the prediction method of the first embodiment. In the example shown in FIG. 13, syntax elements into which prediction is introduced are shown with a delta prefix, but these syntax configurations basically have the same components as the syntax configuration shown in FIG. 12.

  First, a prediction method between 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 reconstruction unit 110B performs prediction processing between the luma_log2_weight_denom and chroma_log2_weight_denom signals using Equation (10), and performs restoration processing using Equation (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 illustrating an example of chroma_log2_weight_denom prediction processing according to the first embodiment.

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

  Subsequently, the index reconstruction unit 110B subtracts luma_log2_weight_denom from chroma_log2_weight_denom (step S102), and sets the difference value as index information in delta_chroma_log2_weight_denom (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 reconstruction unit 110B derives luma_log2_weight_denom already set in the index information as a predicted value (step S201).

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

  Since the fading effect generally has few cases of causing different temporal changes depending on the color space, the fixed-point accuracy for each signal component has a strong correlation between the luminance component and the color difference component. For this reason, it is possible to reduce the amount of information indicating the fixed-point precision by performing prediction in the color space in this way.

  In Equation (10), the luminance component is subtracted from the color difference component, but 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 description will be given of prediction methods for luma_weight_lx [i] and chroma_weight_lx [i] [j] representing the weighting coefficients of the luminance and chrominance signals, respectively. Here, x is an identifier indicating 0 or 1. The values of luma_weight_lx [i] and chroma_weight_lx [i] [j] increase or 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, luma_weight_lx [i] assuming that there is no change in brightness is (1 << 3). On the other hand, when the value of luma_log2_weight_denom is 5, luma_weight_lx [i] assuming that there is no change in brightness is (1 << 5).

  For this reason, the index reconstruction unit 110B performs a prediction process using the weighting coefficient when there is no change in brightness as a reference coefficient (default value). Specifically, the index reconstruction unit 110B performs prediction processing of luma_weight_lx [i] using Equations (12) to (13), and performs restoration processing using Equation (14). Similarly, the index reconstruction unit 110B performs the prediction process of chroma_weight_lx [i] using Expressions (15) to (16), and performs the restoration process using Expression (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 having no change in brightness in the luminance component and the color difference component, respectively.

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

  First, the index reconstruction 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 reconstruction unit 110B subtracts default_luma_weight_lx from luma_weight_lx [i] (step S303), and sets the difference value as index information 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 illustrating an example of luma_weight_lx [i] restoration processing according to the first embodiment.

  First, the index reconstruction 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 reconstruction unit 110B adds delta_luma_weight_lx [i] to default_luma_weight_lx (step S403), and sets the addition value as index information (luma_weight_lx [i]) (step S404).

  Although the flowchart for the luminance component is shown here, the prediction process and the restoration process can be similarly implemented 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 the other images are often normal natural images or images without a fade effect. In this case, the weighting coefficient often takes a case where there is no change in brightness. Therefore, by deriving the initial value when there is no change in brightness from the fixed-point precision and using it as the predicted value, the code amount of the weighting coefficient can be reduced.

  Note that the predicted values of the weighting coefficients (luma_weight_lx [i] and chroma_weight_lx [i] [j]) of the luminance and chrominance signals may be derived with different reference numbers or different POC numbers. In this case, if the reference number closest to the encoding target slice is base_idx, the index reconstruction unit 110B performs prediction processing of luma_weight_lx [i] using Equation (18), and uses Equation (19). Perform the restoration process. Similarly, the index reconstruction unit 110B performs a prediction process of chroma_weight_lx [i] [j] using Expression (20), and performs a restoration process using Expression (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 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 illustrating another example of the luma_weight_lx [i] prediction process according to the first embodiment.

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

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

  Subsequently, the index reconstruction unit 110B subtracts luma_weight_lx [baseidx] from luma_weight_lx [i] (step S503), and sets the difference value as index information in the index information as delta_luma_weight_lx [i] (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 illustrating another example of the luma_weight_lx [i] restoration process according to the first embodiment.

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

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

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

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

  Moreover, you may derive | lead-out the prediction value of the weight coefficient (luma_weight_lx [i] and chroma_weight_lx [i] [j]) of a brightness | luminance and a colour-difference signal using the distance with the encoding reference slice. In this case, the index reconstruction unit 110B performs prediction processing of luma_weight_lx [i] using Equation (22), and performs restoration processing using Equation (23). Similarly, the index reconstruction unit 110B performs a prediction process of chroma_weight_lx [i] [j] using Expression (24), and performs a restoration process using Expression (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.

  Note that the present prediction process and decoding process are equivalent to introducing the i−1th value (i ≠ 0) into baseidx in the flowcharts of FIGS. Although the flowchart for the luminance component is shown here, the prediction process and the restoration process can be similarly implemented for the color difference component (chroma_weight_lx [i] [j]). In addition, here, as an example, the prediction method and restoration method of luma_weight_lx [i] have been described, but prediction and restoration can be similarly performed for luma_offset_lx [i].

  In many cases, the reference slice that can be referred to by the encoding target slice is set to a slice that is close to the encoding target slice in terms of temporal distance or spatial distance from the viewpoint of encoding efficiency. Here, since the luminance change of the slices that are continuous in time and distance has a high correlation, the time-distance correlation of the weight coefficient and the offset is also high. Thus, the amount of codes can be efficiently reduced by predicting the weight coefficient and offset value of the reference slice that are temporally different using the weight coefficient and offset value of the reference slice serving as a reference. Since spatially identical reference slices often have the same weighting factor and offset value, the amount of codes can be reduced by introducing prediction for the same reason.

  Next, a prediction method of 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 expresses the color by the amount of deviation from the median. For this reason, the amount of change from the brightness change in consideration of the median value using the weight coefficient can be used as the predicted value. Specifically, the index reconstruction unit 110B performs a prediction process of chroma_offset_lx [i] [j] using Expressions (26) to (27), and performs a restoration process using Expression (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 with which a 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 illustrating an example of chroma_offset_lx [i] [j] prediction processing according to the first embodiment.

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

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

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

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

  FIG. 21 is a flowchart illustrating an example of the restoration process of chroma_offset_lx [i] [j] according to the first embodiment.

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

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

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

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

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

  Next, H.I. A weight coefficient and a prediction value derivation method with fixed-point accuracy using the 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, a weighting factor is derived according to the temporal distance between reference slices (time ratio of POC number) (offset is 0). As 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 weight coefficient is determined based on the distance ratio. At this time, the fixed-point precision is set to a fixed value of 5.

  For example, H.C. In H.264, a weighting factor is 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 the list 1, POCB is the POC number of the reference image B corresponding to the list 0, and POCT is the POC number of the prediction target image. Clip3 (L, M, N) is a function that performs clip 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 an 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 and list of the prediction target image A difference in the POC number of the reference image corresponding to 0 is shown. These values derive the scaling variable DistScaleFactor at the weighting factor distance. Based on DistScaleFactor, weight coefficients (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 similarly. The index reconstructing unit 110B predicts the fixed-point precision using Equation (30) using the fixed-point precision implicit_log2_weight_denom derived here.

  delta_luma_log2_weight_denom = (luma_log2_weight_denom-implicit_log2_weight_denom)… (30)

  Note that the fixed-point precision of the color difference signal can also be predicted by Expression (30). This value is restored by Equation (31).

  luma_log2_weight_denom = (delta_luma_log2_weight_denom + implicit_log2_weight_denom)… (31)

  Note that the fixed-point precision of the color difference signal can also be restored by the same method as in equation (31).

  Next, the prediction formula of the weight coefficient will be described. Assuming that the implicit weight coefficient is implicit_luma_weight_lx [i], the index reconstruction unit 110B predicts the weight coefficient luma_weight_lx [i] using Expression (32) and restores it using 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 reconstruction unit 110B corrects the weighting coefficient and uses it for prediction depending on whether the fixed-point precision of the 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 predicted value can be derived for the color difference component by using the same method.

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

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

  Subsequently, the index reconstruction unit 110B performs the H.264 operation. In accordance with 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 reconstruction unit 110B determines whether luma_log2_weight_denom is equal to or greater than 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 reconstruction unit 110B subtracts implicit_log2_weight_denom from luma_log2_weight_denom (step S905), and shifts the prediction value to the left by subtracting the value obtained by subtracting implicit_luma_weight_lx [i]. Step S906).

  On the other hand, if luma_log2_weight_denom is not equal to or greater than implicit_log2_weight_denom (No in step S904), the index reconfiguration unit 110B subtracts luma_log2_weight_denom from implicit_log2_weight_denom (step S907), and shifts the prediction value to the right by the value obtained by subtracting implicit_luma_weight_lx [i]. (Step S908).

  Subsequently, the index reconstruction 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 illustrating another example of the luma_weight_lx [i] restoration process according to the first embodiment.

  First, the index reconstruction unit 110B derives luma_log2_weight_denom that has already been set in the index information (step S1001).

  Subsequently, the index reconstruction unit 110B performs the H.264 operation. In accordance with the H.264 implicit weighted prediction derivation method, implicit_log2_weight_denom and implicit_luma_weight_lx [i] are derived (steps S1002 and S1003).

  Subsequently, the index reconstruction unit 110B determines whether luma_log2_weight_denom is equal to or greater than 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 reconstruction unit 110B subtracts implicit_log2_weight_denom from luma_log2_weight_denom (step S1005), and shifts the predicted value to the left by subtracting the value obtained by subtracting implicit_luma_weight_lx [i]. Step S1006).

  On the other hand, if luma_log2_weight_denom is not equal to or greater than implicit_log2_weight_denom (No in step S1004), the index reconfiguration unit 110B subtracts luma_log2_weight_denom from implicit_log2_weight_denom (step S1007), and shifts the prediction value to the right by the value obtained by subtracting it. (Step S1008).

  Subsequently, the index reconstruction unit 110B adds the predicted value derived 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 independently but also in combination. For example, the code amount of the syntax element in the index information is obtained by combining the mathematical formula (10), the mathematical formulas (12) to (13), the mathematical formulas (15) to (16), and the mathematical formulas (26) to (27). Can be efficiently reduced.

  As described above, in the first embodiment, the index setting unit 108 outputs the index information obtained by mapping the WP parameter information to the corresponding syntax configuration, and the index reconstruction unit 110B converts the redundant representation of the syntax element into the slice. Prediction based on the information encoded within. Therefore, according to the first embodiment, it is possible to reduce the code amount as compared with the case where the syntax element is encoded as it is (directly).

  Here, based on the definition order (encoding order) of syntax elements used in the encoding target slice, a prediction value is derived as an intra-screen correlation from already encoded syntax elements, and there is no change in brightness. By deriving a predicted value from a default value that assumes the above, it is possible to make a prediction that makes use of the characteristics of syntax elements, and as a result, there is an effect of reducing the overhead required for encoding syntax elements.

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

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

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

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

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

  As shown in FIG. 24, the decoding apparatus 800 includes a decoding unit 801, an inverse quantization unit 802, an inverse orthogonal transform 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 transform unit 803, the addition unit 804, and the predicted image generation unit 805 are respectively the inverse quantization unit 104, the inverse orthogonal transform unit 105, the addition unit 106, the predicted image generation unit 107, FIG. Are substantially the same or similar elements. Note that 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 performs decoding based on the syntax for each frame or field in order to decode the encoded data. The decoding unit 801 includes an entropy decoding unit 801A and an index reconstruction unit 801B.

  The entropy decoding unit 801A sequentially entropy-decodes the code string of each syntax, such as motion information including a prediction mode, a motion vector, and a reference number, index information for weighted motion compensated prediction, a quantization transform coefficient, and the like. The encoding parameter of the encoding target block is reproduced. Here, the encoding parameters are all parameters necessary for decoding such as information on transform coefficients and information on quantization in addition to the above.

  Specifically, the entropy decoding unit 801A has a function of performing decoding processing such as variable length decoding processing and arithmetic decoding processing on the input encoded data. For example, H.M. In H.264, context-adaptive variable-length coding (CAVLC) and context-adaptive arithmetic coding (CABAC: Context-based Adaptive Arbitrary Coding) are used. 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 reconfiguration unit 801B performs prediction processing according to the characteristics of the syntax element parameters to reduce the code length of the decoded index information syntax element, 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 converts the motion information into 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 to obtain 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 quantization step size derived from the quantization information to obtain a restored transform coefficient. The inverse quantization unit 802 outputs the restored transform coefficient and inputs it to the inverse orthogonal transform unit 803.

  The inverse orthogonal transform unit 803 performs inverse orthogonal transform corresponding to the orthogonal transform performed on the encoding side on the reconstructed transform coefficient input from the inverse quantization unit 802 to obtain a reconstructed prediction error. The inverse orthogonal transform unit 803 outputs the restoration prediction error and inputs it to the addition unit 804.

  The adding unit 804 adds the restored prediction error input from the inverse orthogonal transform unit 803 and the corresponding predicted image to generate a decoded image. The adding unit 804 outputs the decoded image and inputs the decoded image to the predicted image generation unit 805. The adding unit 804 outputs the decoded image to the outside as an output image. The output image is then temporarily stored in an external output buffer (not shown) or the like. For example, in accordance with the output timing managed by the decoding control unit 807, the output image is sent to a display device system or a video device system (not shown). Is output.

  The index setting unit 806 receives the index information input from the decoding unit 801, converts it into WP parameter information, outputs it, and inputs it to the predicted image generation unit 805. Specifically, the index setting unit 806 receives the index information decoded by the entropy decoding unit 801A and reconfigured by the index reconfiguration unit 801B. Then, the index setting unit 806 confirms the list of reference images and the reference number, converts them into WP parameter information, and outputs the converted WP parameter information to the predicted image generation unit 805. Since the WP parameter information has already been described with reference to FIGS. 8A and 8B, description thereof 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 multi-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 storing reference images.

  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 indicates a motion vector indicating a shift amount of motion used in motion compensation prediction, a reference image number, information on a prediction mode such as unidirectional / bidirectional prediction, and the like. The prediction parameter refers to information regarding a motion vector and a prediction mode. Then, the prediction parameter control unit 204 selects and outputs a combination of a reference image number and a prediction parameter used for generating a prediction image 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 for switching which output terminal 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, if the reference image number is 0, the reference image selector 205 connects the output end of FM1 to the output end of the reference image selector 205. If the reference image number is N-1, the reference image selector 205 refers to the output end of the FMN. Connected to the output terminal of the image selector 205. The reference image selector 205 outputs the reference image stored in the frame memory to which the output terminal 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. Note that in the decoding device 800, since the reference image is not used except by the predicted image generation unit 805, 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 a motion compensation prediction process according to the prediction parameter input from the prediction parameter control unit 204 and the reference image input from the reference image selector 205, and generates a unidirectional prediction image. Since motion compensation prediction has already been described with reference to FIG. 5, description thereof will be omitted.

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

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

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

  Here, the details of the multi-frame motion compensation unit 201 will be described with reference to FIG. Similar to 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 a WP application flag and weight information based on the WP parameter information input from the index setting unit 806, inputs the WP application flag to the WP selectors 304 and 305, and weights the weight information. Input to the motion compensation unit 302.

  Here, the WP parameter information includes the fixed-point precision of the weighting factor, the first WP application flag corresponding to the first predicted image, the first weighting factor, the first offset, and the second WP adaptation corresponding to the second predicted image. Contains information on flag, second weighting factor, and 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 information on the fixed point precision of the weight coefficient, the first weight coefficient, the first offset, the second weight coefficient, and the second offset. 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 application flag, a second WP application flag, and weight information, and outputs them. 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, when each WP application flag is 1, the WP selectors 304 and 305 connect each output terminal to the weighted motion compensation unit 302. 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 an average value process based on the two unidirectional predicted images (first predicted image and second predicted image) input from the WP selectors 304 and 305 to generate 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 average value processing 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 and calculates a 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 performs rounding processing by controlling logWDC, which is fixed-point precision, as in Expression (8) when the calculation accuracy of the first predicted image, the second predicted image, and the predicted image is different. Is realized.

  Also, 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 uses the final prediction image based on Equation (9). Is calculated.

  Note that the weighted motion compensation unit 302, when the calculation accuracy of the first prediction image, the second prediction image, and the prediction image is different, uses the log WDC, which is a fixed-point accuracy, as in Expression (8) as in the bidirectional prediction. Rounding processing is realized by controlling to.

  The fixed-point precision of the weighting factor has already been described with reference to FIG. In the case of unidirectional prediction, various parameters (second WP adaptive flag, second weighting factor, and second offset information) corresponding to the second predicted image are not used, and are set to predetermined initial values. May be.

  Decoding section 801 uses syntax 500 shown in FIG. A syntax 500 indicates a structure of encoded data to be decoded by the decoding unit 801. The syntax 500 has already been described with reference to FIG. Also, the picture parameter set syntax 505 has already been described with reference to FIG. 10 except that encoding is decoding, and thus description thereof will be omitted. The slice header syntax 507 has already been described with reference to FIG. 11 except that the encoding is decoding, and thus the description thereof is omitted. Also, the treadweight table syntax 508 has already been described with reference to FIG. 12 except that the encoding is decoding, and thus the description thereof will be omitted.

  Here, the detail of the prediction method of each syntax element relevant to the weighted prediction in a syntax structure is demonstrated. The prediction of syntax elements is performed by the index reconstruction unit 801B. The syntax configuration that explicitly shows the prediction method of the second embodiment is the same as that of the second embodiment, as shown in FIG.

  For the prediction method between the signals of luma_log2_weight_denom and chroma_log2_weight_denom indicating the fixed point precision of the weighting coefficient, restoration processing is performed using Equation (11). The details of the restoration process are as shown in FIG.

  For the prediction method of luma_weight_lx [i] and chroma_weight_lx [i] [j] representing the weighting coefficients of the luminance and chrominance signals, restoration processing is performed using Equations (14) and (17). The details of the restoration process are as shown in FIG.

  For prediction methods for deriving predicted values of luminance and color difference signal weight coefficients (luma_weight_lx [i] and chroma_weight_lx [i] [j]) with different reference numbers or different POC numbers, Equations (19) and (21) are used. The restoration process is performed using the data. The details of the restoration process are as shown in FIG.

  For a prediction method for deriving predicted values of luminance and color difference signal weighting coefficients (luma_weight_lx [i] and chroma_weight_lx [i] [j]) using a distance from a 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−1th value (i ≠ 0) into baseidx in the flowchart of FIG.

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

  The plurality of prediction methods described above can be used not only independently but also in combination. For example, by combining Formula (11), Formula (14), Formula (17), and Formula (28), it is possible to efficiently reduce the code amount of syntax elements in the index information.

  As described above, in the second embodiment, the decoding apparatus 800 eliminates the problem of lowering the coding efficiency by deleting the spatial redundancy using the correlation of the parameters of the information to be coded. The decoding apparatus 800 can reduce the code amount as compared with a conventional configuration in which syntax elements used in weighted motion compensation prediction are encoded as they are (direct values).

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

  In the first to second embodiments described above, the prediction target block size such as a 4 × 4 pixel block, an 8 × 8 pixel block, a 16 × 16 pixel block, and the like has been described as an example, 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. Moreover, it is not necessary to unify all the block sizes within 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 quality of the locally decoded image or the decoded image.

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

  In the first to second embodiments, for the sake of simplification, the luminance signal and the weighted motion compensation prediction process for the color difference signal are not distinguished from each other, and the comprehensive explanation is described regarding the color signal component. However, when the weighted motion compensation prediction process is different between the luminance signal and the color difference signal, the same or different weighted motion compensation prediction process may be used. If a weighted motion compensation prediction process that is different between the luminance signal and the color difference signal is used, the weighted motion compensation prediction process selected for the color difference signal can be encoded or decoded in the same manner as the luminance signal.

  In the first and second embodiments, syntax elements not defined in this embodiment can be inserted between the rows of the table shown in the syntax configuration, and other conditional branch descriptions are included. It does not matter. Alternatively, the syntax table can be divided and integrated into a plurality of tables. Moreover, 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 embodiment realizes highly efficient weighted motion compensation prediction processing while solving the problem of encoding redundant information of syntax structure when performing weighted motion compensation prediction. Therefore, according to each embodiment, the encoding efficiency is improved, and the subjective image quality is also improved.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example 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 scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

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

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

DESCRIPTION OF SYMBOLS 100 Coding apparatus 101 Subtraction part 102 Orthogonal transformation part 103 Quantization part 104 Inverse quantization part 105 Inverse orthogonal transformation part 106 Adder part 107 Predictive image generation part 108 Index setting part 109 Motion evaluation part 110 Coding part 110A Entropy coding part 110B Index reconstruction unit 111 Coding control unit 201 Multiple frame motion compensation unit 202 Memory 203 Unidirectional motion compensation unit 204 Prediction parameter control unit 205 Reference image selector 206 Frame memory 207 Reference image control unit 301 Default motion compensation unit 302 Weighted motion Compensation unit 303 WP parameter control unit 304, 305 WP selector 800 decoding device 801 decoding unit 801A entropy decoding unit 801B index reconstruction unit 802 inverse quantization unit 803 inverse orthogonal transform unit 804 Calculation unit 805 predicted image generator 806 index setting unit 807 the decoding control unit

Claims (22)

An electronic device to which encoded data is input,
Decoding the first fixed-point precision of the luminance weighting factor from the encoded data;
Decoding the first difference value, which is the same value as the difference between the first fixed-point precision and the second fixed-point precision of the color difference weight coefficient, from the encoded data;
Determining the second fixed-point precision by adding the first fixed-point precision and the first difference value;
Determining the same value as the value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision as the first reference value of the luminance weighting coefficient;
Decoding the 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, from the encoded data;
By adding the first reference value and the second difference value, the luminance weighting factor is determined,
A second reference value of the color difference weighting coefficient is determined by a value obtained by left-shifting “1” by the number of bits determined by the second fixed-point precision;
Decoding the third difference value of the color difference weighting coefficient, which is the same value as the difference between the color difference weighting coefficient and the second reference value, from the encoded data;
An electronic apparatus comprising a processing unit that determines a weight coefficient of the color difference by adding the second reference value and the third difference value. The processor is
By subtracting the value obtained by multiplying the median by a color difference weighting factor and right shifting by the number of bits determined by the second fixed-point precision, from the median of the maximum pixel values, Calculate the third reference value of the color difference offset,
Decoding the fourth difference value of the color difference offset, which is the same value as the difference between the color difference offset and the third reference value, from the encoded data;
The electronic device according to claim 1, wherein the offset of the color difference is determined by adding the third reference value and the fourth difference value. The processor is
Decoding the luminance offset from the encoded data;
A predicted luminance value is determined by at least using the integration of the luminance weight coefficient with the luminance value of the reference image, the right shift of the number of bits determined by the first fixed-point precision, and the addition of the luminance offset. And
Prediction value of color difference using at least the integration of the color difference value of the reference image with the weight coefficient of the color difference, the right shift of the number of bits determined by the second fixed-point precision, and the addition of the offset of the color difference The electronic device according to claim 1, wherein the electronic device is determined. The processor is
Decoding transform coefficients from the encoded data;
Using at least an inverse transform to the transform coefficients to determine a prediction error value;
The electronic apparatus according to claim 3, wherein a decoded image is generated using the predicted luminance value, the predicted color difference value, and the prediction error value.   The value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision is a luminance weight coefficient used when there is no change in luminance between the reference image and the target image. The electronic device according to any one of claims 1 to 4, wherein the electronic device has the same value as the value. The processor is
Decoding a motion vector from the encoded data;
The electronic device according to claim 3, wherein the reference image is generated based on the motion vector. A receiving unit for receiving the encoded data via a communication line;
A buffer for temporarily storing at least a part of the encoded data,
The processing unit reads at least a part of the encoded data from the buffer and sequentially decodes parameters included in the encoded data,
The electronic device according to claim 1, wherein the processing unit is a CPU (Central Processing Unit). A receiving unit for receiving the encoded data via a communication line;
A buffer for temporarily storing at least a part of the encoded data,
The processing unit reads at least a part of the encoded data from the buffer and sequentially decodes parameters included in the encoded data,
The electronic device according to claim 1, wherein the processing unit is a DSP (Digital Signal Processor) or an FPGA (Field Programmable Gate Array). Inputting encoded data; and
Decoding the first fixed point precision of the luminance weighting factor from the encoded data;
Decoding the first difference value, which is the same value as the difference between the first fixed-point precision and the second fixed-point precision of the color difference weighting coefficient, from the encoded data;
Determining the second fixed-point precision by adding the first fixed-point precision and the first difference value;
Determining a value equal to a value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision as a first reference value of the luminance weighting factor;
Decoding from the encoded data a second difference value of the luminance weighting factor that is the same value as the difference between the luminance weighting factor and the first reference value;
Determining a weighting factor for the luminance by adding the first reference value and the second difference value;
Determining a second reference value of the color difference weighting coefficient based on a value obtained by left-shifting “1” by the number of bits determined by the second fixed-point precision;
Decoding a third difference value of the color difference weighting coefficient that is the same value as the difference between the color difference weighting coefficient and the second reference value from the encoded data;
Determining a weight coefficient of the color difference by adding the second reference value and the third difference value;
A decoding method including: By subtracting the value obtained by multiplying the median by a color difference weighting factor and right shifting by the number of bits determined by the second fixed-point precision, from the median of the maximum pixel values, Calculating a third reference value of the color difference offset;
Decoding the fourth difference value of the color difference offset, which is the same value as the difference between the color difference offset and the third reference value, from the encoded data;
Determining an offset of the color difference by adding the third reference value and the fourth difference value;
The decoding method according to claim 9, further comprising: Decoding a luminance offset from the encoded data;
A predicted luminance value is determined by at least using the integration of the luminance weight coefficient with the luminance value of the reference image, the right shift of the number of bits determined by the first fixed-point precision, and the addition of the luminance offset. And steps to
Prediction value of color difference using at least the integration of the color difference value of the reference image with the weight coefficient of the color difference, the right shift of the number of bits determined by the second fixed-point precision, and the addition of the offset of the color difference A step of determining
The decoding method according to claim 9 or 10, further comprising: Decoding transform coefficients from the encoded data;
Determining a prediction error value using at least an inverse transform to the transform coefficient;
Generating a decoded image using the predicted luminance value, the predicted color difference value, and the prediction error value;
The decoding method according to claim 11, further comprising:   The value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision is a luminance weight coefficient used when there is no change in luminance between the reference image and the target image. The decoding method according to any one of claims 9 to 12, which is the same value as the value. Decoding a motion vector from the encoded data;
Generating the reference image based on the motion vector;
The decoding method according to any one of claims 11 to 13, further comprising: A receiving unit receiving the encoded data via a communication line;
A buffer temporarily storing at least a portion of the encoded data;
A processing unit further comprising: reading at least a part of the encoded data from the buffer and sequentially decoding parameters included in the encoded data;
The decoding method according to claim 9, wherein the processing unit is a CPU (Central Processing Unit). A receiving unit receiving the encoded data via a communication line;
A buffer temporarily storing at least a portion of the encoded data;
A processing unit further comprising: reading at least a part of the encoded data from the buffer and sequentially decoding parameters included in the encoded data;
The decoding method according to any one of claims 9 to 14, wherein the processing unit is a DSP (Digital Signal Processor) or an FPGA (Field Programmable Gate Array). Inputting encoded data; and
Decoding the first fixed point precision of the luminance weighting factor from the encoded data;
Decoding the first difference value, which is the same value as the difference between the first fixed-point precision and the second fixed-point precision of the color difference weighting coefficient, from the encoded data;
Determining the second fixed-point precision by adding the first fixed-point precision and the first difference value;
Determining a value equal to a value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision as a first reference value of the luminance weighting factor;
Decoding from the encoded data a second difference value of the luminance weighting factor that is the same value as the difference between the luminance weighting factor and the first reference value;
Determining a weighting factor for the luminance by adding the first reference value and the second difference value;
Determining a second reference value of the color difference weighting coefficient based on a value obtained by left-shifting “1” by the number of bits determined by the second fixed-point precision;
Decoding a third difference value of the color difference weighting coefficient that is the same value as the difference between the color difference weighting coefficient and the second reference value from the encoded data;
Determining a weight coefficient of the color difference by adding the second reference value and the third difference value;
A program that causes a computer to execute. By subtracting the value obtained by multiplying the median by a color difference weighting factor and right shifting by the number of bits determined by the second fixed-point precision, from the median of the maximum pixel values, Calculating a third reference value of the color difference offset;
Decoding the fourth difference value of the color difference offset, which is the same value as the difference between the color difference offset and the third reference value, from the encoded data;
Determining an offset of the color difference by adding the third reference value and the fourth difference value;
The program according to claim 17, further causing the computer to execute. Decoding a luminance offset from the encoded data;
A predicted luminance value is determined by at least using the integration of the luminance weight coefficient with the luminance value of the reference image, the right shift of the number of bits determined by the first fixed-point precision, and the addition of the luminance offset. And steps to
Prediction value of color difference using at least the integration of the color difference value of the reference image with the weight coefficient of the color difference, the right shift of the number of bits determined by the second fixed-point precision, and the addition of the offset of the color difference A step of determining
19. The program according to claim 17 or 18 for causing the computer to execute the following. Decoding transform coefficients from the encoded data;
Determining a prediction error value using at least an inverse transform to the transform coefficient;
Generating a decoded image using the predicted luminance value, the predicted color difference value, and the prediction error value;
The program according to claim 19, further causing the computer to execute.   The value obtained by left-shifting “1” by the number of bits determined by the first fixed-point precision is a luminance weight coefficient used when there is no change in luminance between the reference image and the target image. The program according to any one of claims 17 to 20, which is the same value as the value. Decoding a motion vector from the encoded data;
Generating the reference image based on the motion vector;
The program according to claim 19, further causing the computer to execute.