Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
  • H04N19/13—Adaptive entropy coding, e.g. adaptive variable length coding [AVLC] or context adaptive binary arithmetic coding [CABAC]
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
  • G06F17/10—Complex mathematical operations
  • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
  • H04N19/129—Scanning of coding units, e.g. zig-zag scan of transform coefficients or flexible macroblock ordering [FMO]
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
  • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
  • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
  • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
  • H04N19/18—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a set of transform coefficients
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
  • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
  • H04N19/91—Entropy coding, e.g. variable length coding [VLC] or arithmetic coding

Definitions

• the present principles generally relate to picture/video encoding and decoding. Particularly, the technical field of the present principles are related to context-adaptive binary arithmetic coding a sequence of binary symbols representing video data or syntax elements required for decoding said video data.
• video data contains one or several arrays of samples (pixel values) in a specific picture/video format which specifies all information relative to the pixel values of a picture (or a video) and all information which may be used by a display and/or any other device to visualize and/or decode a picture (or video) for example.
• a still picture (or a picture of a video) comprises at least one component, in the shape of a first array of samples, usually a luma (or luminance) component, and, possibly, at least one other component, in the shape of at least one other array of samples, usually a color component.
• the same information may also be represented by a set of arrays of color samples, such as the traditional tri-chromatic RGB representation.
• a pixel value is a video data that may be represented by a vector of C values, where C is the number of components. Each value of a vector is represented with a number of bits which defines a maximal dynamic range of the pixel values.
• a block means a set of elements such video data or syntax elements relative to video data.
• a block of pixels is a set of pixels which belong to a picture and the pixel values of a block means the values of the pixels which belong to this block.
• a video coding device may attempt to compress video data by taking advantage of spatial and temporal redundancy.
• a video encoder may take advantage of spatial redundancy by coding a block relative to neighboring, previously coded blocks.
• a video encoder may take advantage of temporal redundancy by coding a block of picture data relative to data of previously coded picture.
• the video encoder may predict a current block of video data from data of a spatial neighbor or from data of a previously coded picture.
• the video encoder may then calculate a residual for the block of video data as a difference between the actual pixel values for the block of video data and the predicted pixel values for the block.
• the residual for a block may include pixel-by-pixel difference values in the pixel (or spatial) domain.
• the video encoder may then apply a transform to the values of the residual to compress energy of the pixel values into a relatively small number of transform coefficients in the frequency domain.
• the video encoder may then quantize the transform coefficients, scan the quantized transform coefficients to convert a two-dimensional matrix of quantized transform coefficients into a one-dimensional vector including the quantized transform coefficients.
• the video encoder may then apply an entropy coding process to entropy encode the scanned coefficients.
• Example entropy coding processes may include, for example, context-adaptive variable length coding (CAVLC), context-adaptive binary arithmetic coding (CABAC), syntax-based context- adaptive binary arithmetic coding (SBAC), probability interval partitioning entropy (PIPE) coding or other entropy encoding methodologies.
• CAVLC context-adaptive variable length coding
• CABAC context-adaptive binary arithmetic coding
• SBAC syntax-based context- adaptive binary arithmetic coding
• PIPE probability interval partitioning entropy
• a video decoder may perform generally reciprocal techniques to the encoding techniques performed by the video encoder. Although generally reciprocal, the video decoder may, in some instances, perform techniques similar to those performed by the video encoder.
• the video encoder may also entropy encode syntax elements associated with the encoded video data for use by a video decoder in decoding the video data.
• the video decoder may then rely on syntax elements or other data contained in a received bitstream that includes the data described with respect to the video encoder.
• the positions of the significant coefficients (i.e., nonzero transform coefficients) in a block of video data may be encoded prior to the values of the transform coefficients, which may be referred to as the "levels" of the transform coefficients.
• the process of coding the locations of the significant coefficients may be referred to as significance map coding.
• a significance map (SM) includes a two dimensional array of binary values that indicate locations of significant coefficients.
• a SM for a block of video data may include a two- dimensional array of ones and zeros, in which the ones indicate positions of significant transform coefficients within the block and the zeros indicate positions of non-significant (zero-valued) transform coefficients within the block.
• the ones and zeros are referred to as "significant coefficient flags.”
• the SM may include another 2-D array of ones and zeros, in which a one indicates a position of a last significant coefficient within the block according to a scanning order associated with the block, and the zeros indicate positions of all other coefficients within the block.
• the ones and zeros are referred to as "last significant coefficient flags.”
• the last significant coefficient in a block may be coded first, before sending the rest of the SM.
• SM coding for a block of video data may consume a significant percentage of the video bitrate used to code the block.
• a video coder may entropy code the level of each transform coefficient. For example, a video coder may convert an absolute value of each non-zero transform coefficient into binary form. In this way, each non-zero transform coefficient may be "binarized,” e.g., using a unary code comprising one or more bits, or "bins". A bit for the sign of the transformed coefficient may also be encoded.
• binarized syntax element may represent motion vector residuals, Trnasform Unit coding flags, Coding Group coding flags, transformed coefficient significant flags, transformed coefficient magnitude (greater than 1 and greater than 2) flags, SAO data, etc.
• a video coder may entropy code each binary symbol (or bin) for a block of video data, whether corresponding to transform coefficients or syntax element (information) for the block, using probability estimates for each binary symbol.
• the probability estimates may indicate a likelihood of a binary symbol having a given binary value (e.g., "0" or "1 ").
• the probability estimates may be included within a probability model, also referred to as a "context model.”
• a video coder may determine a context for a binary symbol to be coded and select a probability model from the determined context.
• Context for a binary symbol of a sequence of binary symbols representing a syntax element, may include values of related binary symbols of previously coded neighboring syntax elements.
• the context for each significant coefficient flag of the block includes a type of the block (e.g., block size, block of lum or chroma elements), and a position of a coefficient corresponding to the respective flag within the block according to a scanning order associated with the block.
• a type of the block e.g., block size, block of lum or chroma elements
• the context for a binary symbol of a binarized residual transform coefficient absolute value for the block includes a position of the binary symbol within a unary codeword that represents the absolute value, and values of previously coded coefficients of the block.
• the context for a binary symbol of a sequence of binary symbols representing a coded block pattern includes values of related binary symbols of previously coded neighboring syntax elements, e.g., on the top and to the left of the current syntax element.
• the probability model After having entropy coded a binary symbol, the probability model is updated according to the value of the coded binary symbol to reflect the most current probability estimates.
• the binary symbols associated with a block of video data may be coded in one or more coding "passes." For example, during a first pass, a video coder may entropy code the SM. During a second pass, the video coder may entropy code a first bin of the transform coefficient levels. The video coder may continue to perform coding passes until all of the information associated with the transform coefficients of a block is coded.
• the video coder may code the bins of a block of video data (or syntax elements) using a combination of context adaptive and non-context adaptive coding. For example, for one or more passes, the video coder may use a bypass mode to bypass, or omit, the regular arithmetic coding process. In such instances, a fixed equal probability model may be used to code a bypass coded bin. Bypass coded bins do not include context or probability updates.
• context which indicates a particular probability model for coding a binary symbol
• context may be influenced by values of previously coded binary symbols, e.g., related binary symbols of previously coded syntax elements.
• the probability models used to code the binary symbols may also be influenced by values of previously coded binary symbols. That is, the probability models may be maintained as a state in a finite state machine. Each particular state may correspond to a specific probability value. The next state, which corresponds to an update of the probability model, may depend on the value of the current binary symbols (e.g., the bin currently being coded).
• a particular probability model may be maintained as a state in a finite state machine, with each particular state corresponding to a specific probability value.
• the next state which corresponds to an update of the probability model, may depend on the value of the current binary symbol.
• Such feedback loops which may be referred to as state updates, may present a computational bottleneck. For example, it may be difficult to increase throughput due to the dependencies in the feedback loops. That is, one binary symbol may not be processed until the probability model from the previous binary symbol has been updated.
• the same context may be called continuously (binary symbol by binary symbol) with high frequency.
• Context-adaptive binary arithmetic coding is a form of entropy encoding used in the H.264/MPEG-4 AVC ⁇ "Advanced video coding for generic audiovisual Services", SERIES H: AUDIOVISUAL AND MULTIMEDIA SYSTEMS, Recommendation ITU-T H.264, Telecommunication Standardization Sector of ITU, February 2014) and High Efficiency Video Coding (HEVC) standards ⁇ "High Efficiency Video Coding", SERIES H:
• CABAC is a lossless compression technique, although the video coding standards in which it is used are typically for lossy compression applications.
• Fig. 1 shows a generic block diagram for encoding a syntax element
• CABAC comprises three elementary steps.
• a binarizer maps a given non-binary valued syntax element to a sequence of binary symbols (bin).
• this initial step is bypassed, as shown in Fig. 1 .
• a context value is determined depending on previously encoded syntax elements or coded binary symbols. Then, the context value and the value of the binary symbol s are passed to a regular coding engine, where the final stage of arithmetic encoding together with a subsequent context updating takes place base on the probability p of the context value (see Fig. 1 ).
• bypass coding mode is chosen for binary symbols in order to allow a speedup of the whole encoding (and decoding) process by means of a simplified coding engine without the usage of an explicitly assigned probability model, as illustrated by the lower right branch of the switch in Fig. 1.
• Fig. 2 illustrates an example of the context selecting stage when a sequence of binary symbols representing a significance map relative to a block of video data.
• a block of binary symbols, representing a block of the significance map is represented.
• This block is scanned according to a specific scanning order.
• the scanning order illustrated by the dotted lines, starts from the bottom-right corner to the top-left corner of the block.
• several contexts C are defined for the binary symbol s according to said scanning order and each context C, is associated with a context value ContVal,.
• Each context Ci is defined according to the binary values of x1 and x2 and a specific context value ContVal, is assigned to each of the context.
• a context value comprises a bit valMPS representing a specific binary value, so-called Most Probable Symbols (MPS), of the binary symbol s and bits (e.g. 7 bits) pStatldx representing a probability p' (or state) from which a probability p is deduced.
• MPS Most Probable Symbols
• a context Cs is selected from the four contexts and the associated context value ContVals is assigned to the binary symbol s.
• the update of the context value ContVals is made following the process illustrated in Fig. 4 depending on whether or not the binary symbol s equals MPS.
• transldxMPS if the binary symbol s is the MPS
• transldxLPS if the binary symbol s is not the MPS, i.e. it is the Least Probable Symbol (LPS)
• the probability PMPS of the binary symbol s to be the MPS is quantized linearly on 8 bits, from 0 to 1 27. It is deduced from the selected context value by
• Context-Adaptive coding is a powerful tool that allows to follow dynamically the statistics of the different syntax elements relative to encoded video data.
• CABAC CABAC for entropy coding video data and/or syntax elements relative to video data
• One of the challenge is thus to benefit from the increased compression capability provided by CABAC without increasing too much the number of contexts.
• the present principles relate to a device for context-adaptive binary arithmetic coding a sequence of binary symbols representing a syntax element related to video data or a syntax element relative to a video data comprising a processor configured to, for each binary symbol of the sequence of binary symbols:
• - obtain a context value from a context model defined for the binary symbol, said context value comprising bits representing the probability, called a first probability p, for the binary symbol to be equal to a binary value;
• the context value further comprises a bit representing a most probable binary value of the binary symbol and the bits represent the first probability p for the binary symbol to be equal to said most probable binary value.
• determining the second probability p' by modifying the first probability p according to at least one previously coded binary symbol of the sequence of binary symbols comprises:
• the probability adjusting value is obtained from a weighted value of said at least one previously coded binary symbol of the sequence of binary symbols by:
• ⁇ 0 is a constant value
• w j is a weighting value associated with said at least one of previously coded binary symbol of the sequence of binary symbols
• f j is the value of said at least one previously coded binary symbol of the sequence of binary symbols.
• the probability adjusting value is selected from a set of potential values, each defined according to the values of at least one previously coded binary symbol of the sequence of binary symbols.
• the present principles relate to a method for encoding or decoding video data comprising the steps of one of the above method for context-adaptive binary arithmetic coding a sequence of binary symbols representative of said video data.
• the present principles relate to a device for encoding or decoding video data or syntax element comprising a processor configured to context-adaptive binary arithmetic code a sequence of binary symbols representative of said video data by: - obtaining a context value from a context model defined for the binary symbol, said context value comprising bits representing the probability, called a first probability p, for the binary symbol to be equal to a binary value;
• the weighting value associated with a previously coded binary symbol of the sequence of binary symbols depends on the Euclidean distance from the current binary symbol of the sequence of binary symbols to be coded.
• the present principles relate to a computer program product comprising program code instructions to execute the steps of the above method when this program is executed on a computer and a non-transitory storage medium carrying instructions of program code for executing steps of the above method when said program is executed on a computing device.
• Fig. 1 shows a generic block diagram for encoding a syntax element using CABAC
• Fig. 2 illustrates an example of the context selecting stage when a sequence of binary symbols representing a significance map relative to a block of video data
• - Fig. 3 shows an example of a context value
• FIG. 4 shows a generic block diagram for updating a context value
• FIG. 6 illustrates a method for context-adaptive binary arithmetic coding a binary symbol s of a sequence of binary symbols in accordance with an example of the present principles
• Fig. 7 illustrates an example of an embodiment of the method of Fig. 6 when the binary symbol s represents, for example, a significance flag of a significance map relative to a block of video data;
• FIG. 8 illustrates an example of the method for context-adaptive binary arithmetic coding a binary symbol s in accordance with an example of the present principles when the binary symbol represents the so-called "greater than one" flag;
• FIG. 9 shows a block diagram of a method for encoding a block of pixels in accordance with the present principles
• FIG. 10 shows a block diagram of a method for decoding a block of pixels in accordance with the present principles
• FIG. 11 shows an example of an architecture of a device in accordance with an example of present principles.
• FIG. 12 shows two remote devices communicating over a communication network in accordance with an example of present principles.
• each block represents a circuit element, module, or portion of code which comprises one or more executable instructions for implementing the specified logical function(s).
• the function(s) noted in the blocks may occur out of the order noted. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending on the functionality involved.
• the present principles are described for encoding/decoding a picture but extends to the encoding/decoding of a sequence of pictures (video) because each picture of the sequence is sequentially encoded/decoded as described below.
• the present principles disclose a modified version of CABAC in which a single context for a binary symbol is considered, a probability p' is obtained by modifying the probability p included in the context value relative to said single context, instead of selecting a context among a set of potential contexts as in prior art.
• the modified probability p' of the context value and the value of the binary symbol s are provided to the arithmetic encoding, and the context is updated based on the probability p.
• the number of context values to maintain in memory is thus reduced compared to prior art. Then, the number of contexts may be reduced according to the present principles without a significant loss of the usual CABAC performance.
• Fig. 6 illustrates a method for context-adaptive binary arithmetic coding a binary symbol s of a sequence of binary symbols in accordance with an example of the present principles.
• step 100 a context value ContVal is obtained from a context C defined for the binary symbol s.
• said context value ContVal may comprise a bit representing a most probable binary value (MPS) of the binary symbol s and bits representing the probability p for the binary symbol to be equal to said most probable binary value.
• MPS most probable binary value
• the context C is selected from a set of potential contexts Ci as explained above in relation with Fig. 1.
• the single context C is available for a binary symbol s.
• a probability p' is determined by modifying the probability p according to some information data representative of previously coded image data.
• the information data is at least one previously coded binary symbol of the sequence of binary symbols.
• the information data is provided by a finite-state machine that evolves according to the successive coding of binary symbols.
• the binary symbol is arithmetic coded based on the probability p' and in step 130, the context value ContVal is updated according to the coded binary symbol, i.e. as described in relation with Fig. 4.
• the probability p' is determined by modifying the probability p comprises:
• step 1 1 1 a probability adjusting value A from said at least one previously coded binary symbol of the sequence of binary symbols;
• step 1 12 determining (step 1 12) the probability p' by adding said probability adjusting value to the probability p:
• C is a sub-context defined from at said at least one previously coded syntax element.
• Fig. 7 illustrates an example of such an embodiment of the method when the binary symbol s represents, for example, a significance flag of a significance map.
• a context value Contval is obtained from a context defined by the two coded syntax elements x1 and x2 as defined in relation with Fig. 2.
• a sub-context C is defined from at least one other previously coded binary symbol of the sequence of binary symbols, here x3, x4 and x5.
• the sub-context C is considered to obtain the adjusting value ⁇ .
• the probability adjusting value ⁇ is obtained by the following equation:
• ⁇ 0 is a constant value
• w j is a weighting value associated with one of the K previously coded syntax elements defining the sub-context C
• ⁇ is the value of said K previously coded syntax element.
• the constant value ⁇ 0 may be adjusted such that the expected value, taken over all combinations of the f j 's, of ⁇ is close to zero. This ensures that the global statistical behavior of the sub-contexts C considered together is close to the statistical behavior of the context C.
• the weighting value w,- associated with a syntax element xj depends on the Euclidean distance from the binary symbol s.
• the probability adjusting value ⁇ is a fixed and predetermined value which is selected from a set of potential values, each defined according to the values of at least one previously coded binary symbol of the sequence of binary symbols.
• a positive probability adjusting value may be determined when all the x3, x4 and x5 syntax elements equal 1 and a negative value may be determined when all these syntax elements equal 0.
• a positive probability adjusting value may be selected when at least one syntax elements belonging to the sub-context C equal 1 and a negative probability adjusting value may be selected when at least one syntax elements belonging to the sub-context C equal 0.
• 8 probability adjusting values may be determined, each according to the percentage of 1 or 0 of the syntax elements x3, x4 and x5.
• the probability adjusting value ⁇ is selected from a set of potential values, each defined according to the values of at least one previously coded binary symbol of the sequence of binary symbols.
• the probability adjusting values may be optimized depending on, for instance, the Quantization Parameter (QP) of the binary symbol to code. For example, by using a test set of video sequences to code at a given QP and testing various values of the weights w s , optimized values of said w/s are determined and hard-coded in the video coder.
• QP Quantization Parameter
• Fig. 8 illustrates an example of the method for context-adaptive binary arithmetic coding a binary symbol s in accordance with an example of the present principles when the binary symbol represents the so-called "greater than one" flag, in short greaterl flag, that signals if a transformed coefficient absolute value is strictly greater than one or not. Of course, it applies only to a significant coefficient (i.e. signaled as non-zero by the significance flag).
• a context value is chosen among four contexts as described in relation with Fig. 2.
• a context index is used for determining which of these four contexts is selected.
• the context is initialized to 1 and is updated as follows: As soon as a last coded greaterl flag (syntax element) equals 1 (is true), the context index becomes 0; otherwise the context index is incremented up to 3. The greaterl flag is then encoded based on the probability included in the context value associated with the selected context and the selected context is updates as explained above.
• the greaterl flags may be coded using the modified CABAC described in relation with Fig. 6.
• step 100 a context C is chosen among four contexts as described in relation with Fig. 2.
• a probability p is then obtained from the context value ContVals associated with this context Cs.
• a probability adjusting value is then determined according to the at least one previously coded greaterl flag, a modified probability p' is obtained according to said probability adjusting value, the current greaterl flag is coded based on the modified probability p' and the context value ContVals is updated according to the probability p as explained above.
• the same method may be applied to the "greater than two" flag.
• Fig. 9 shows a block diagram of a method for encoding a block Be of video data or syntax element in accordance with the present principles.
• a module extracts, for example on a pixel base, a prediction block Bpred from the current block Be to generate a residual block Bres.
• a module transforms and quantifies the residual block Bres.
• the transform T is, for example, a Discrete Cosinus Transform (DCT) or any other block-based transform such a wavelet-based.
• DCT Discrete Cosinus Transform
• a module implements the inverse operations: inverse quantization Q 1 followed by an inverse transform T ⁇ 1 .
• a module entropy encodes the quantified data to a bitstream F of coded data.
• This module implements the modified CABAC as described in relation with Fig. 6 and 7.
• a module merges, for example on a pixel base, the block outputting the step 1206 and the prediction block Bpred to generate a block of reconstructed video data (or syntax element) which is stored in a memory (step 1210).
• a module estimates at least one motion vector between the block of video data Be and a block of a reference picture Ir stored in a memory (step 1210), this reference picture having been coded and reconstructed.
• the motion estimation may be executed between the block of video data Be and a block of video data of an original reference picture lc. In that case, the step 1 210 is not linked to the step 121 2.
• the motion estimation searches in the reference picture Ir (or lc) a motion data, such for example a motion vector, in order to minimize an error computed between a block of video data Be and a block of video data in that reference picture identified by the motion data.
• a motion data such for example a motion vector
• the motion data are then transmitted to a decision module.
• the decision module selects a coding mode for the block of video data Be from a set of determined coding modes.
• the selected coding mode is for example the coding mode which minimizes a criterion such a rate- distorsion based criterium.
• the present principles are not limited to any process to select a coding mode which may be selected using any other criterium.
• the selected coding mode and the motion data are syntax elements which are entropy encoded in the signal F (step 1204).
• a module determines the prediction block Bpred from the selected coding mode outputting the decision module (step1214) and, potentially, from motion data outputting a memory (step 1210 or 1212).
• Fig. 10 shows an embodiment of a method for decoding a bitstream F of coded video data representing a block of video data.
• the bitstream F of coded video data (including syntax elements), for example, has been obtained from a method as described in relation with Fig. 9 and transmitted via a communication path.
• a module implements a usual CABAC for entropy decoding, from the bitstream F, residual data relative to coded video data to decode, and syntax elements required for reconstructing the decoded video data for the residual data such coding modes, motion data or significant map for example.
• decoding motion data comprises motion estimating.
• This solution to decode the motion data may be the so-called template process in the prior art.
• the decoded video data relative to the block of pixels to decode are then transmitted to a module (step 1302) which applies an inverse quantizing followed by an inverse transform.
• the module in step 1302 is identical to the module in step 1206.
• the step 1302 is linked to the step 1304 which merges, for example on a pixel by pixel base, the residual block outputting the step 1302 and a prediction block to generate a decoded block of video data Be (also said reconstructed block) which is then stored in a memory (step 1306).
• a module determines a prediction block Bpred from the coding mode extracted from the bistream F for the block of video data to decode, and potentially, from motion data determined outputting the module which reconstructs the motion data.
• the decoder described in relation with Fig. 10 is configured to decode video data which have been encoded by the encoder described in relation with Fig. 9.
• the encoder (and decoder) is not limited to a specific encoder (decoder).
• the encoder (and decoder) is not limited to a specific encoder which may be, for example, an image/video coder with loss like JPEG, JPEG2000, MPEG2, HEVC or H264/AVC standards.
• the modules are functional units, which may or not be in relation with distinguishable physical units. For example, these modules or some of them may be brought together in a unique component or circuit, or contribute to functionalities of a software. A contrario, some modules may potentially be composed of separate physical entities.
• the apparatus which are compatible with the present principles are implemented using either pure hardware, for example using dedicated hardware such ASIC or FPGA or VLSI, respectively « Application Specific Integrated Circuit » , « Field-Programmable Gate Array » « Very Large Scale Integration » or from several integrated electronic components embedded in a device or from a blend of hardware and software components.
• Fig. 11 represents an exemplary architecture of a device 1 100 which may be configured to implement a method described in relation with Fig. 1-10.
• Device 1 100 comprises following elements that are linked together by a data and address bus 1 101 :
• microprocessor 1 102 (or CPU), which is, for example, a DSP (or Digital Signal Processor);
• DSP Digital Signal Processor
• ROM Read Only Memory
• the battery 1 106 is external to the device.
• the word « register » used in the specification can correspond to area of small capacity (some bits) or to very large area (e.g. a whole program or large amount of received or decoded data).
• the ROM 1 103 comprises at least a program and parameters.
• the ROM 1 103 may store algorithms and instructions to perform techniques in accordance with present principles. When switched on, the CPU 1 102 uploads the program in the RAM and executes the corresponding instructions.
• RAM 1 104 comprises, in a register, the program executed by the CPU 1 1 02 and uploaded after switch on of the device 1 100, input data in a register, intermediate data in different states of the method in a register, and other variables used for the execution of the method in a register.
• the implementations described herein may be implemented in, for example, a method or a process, an apparatus, a software program, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method or a device), the implementation of features discussed may also be implemented in other forms (for example a program).
• An apparatus may be implemented in, for example, appropriate hardware, software, and firmware.
• the methods may be implemented in, for example, an apparatus such as, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants ("PDAs”), and other devices that facilitate communication of information between end-users.
• PDAs portable/personal digital assistants
• the block Be of video data or syntax element or the sequence of binary symbols is obtained from a source.
• the source belongs to a set comprising:
• a local memory (1 103 or 1 1 04), e.g. a video memory or a RAM (or Random Access Memory), a flash memory, a ROM (or Read Only Memory
• a storage interface (1 105), e.g. an interface with a mass storage, a RAM, a flash memory, a ROM, an optical disc or a magnetic support;
• a communication interface (1 105), e.g. a wireline interface (for example a bus interface, a wide area network interface, a local area network interface) or a wireless interface (such as a IEEE 802.1 1 interface or a Bluetooth® interface); and - an picture capturing circuit (e.g. a sensor such as, for example, a CCD (or Charge-Coupled Device) or CMOS (or Complementary Metal-Oxide-Semiconductor)).
• a wireline interface for example a bus interface, a wide area network interface, a local area network interface
• a wireless interface such as a IEEE 802.1 1 interface or a Bluetooth® interface
• an picture capturing circuit e.g. a sensor such as, for example, a CCD (or Charge-Coupled Device) or CMOS (or Complementary Metal-Oxide-Semiconductor)
• the decoded data is sent to a destination; specifically, the destination belongs to a set comprising:
• a local memory (1 1 03 or 1 104), e.g. a video memory or a RAM, a flash memory, a hard disk ;
• a storage interface (1 105), e.g. an interface with a mass storage, a RAM, a flash memory, a ROM, an optical disc or a magnetic support;
• a communication interface (1 105) e.g. a wireline interface (for example a bus interface (e.g. USB (or Universal Serial Bus)), a wide area network interface, a local area network interface, a HDMI (High Definition Multimedia Interface) interface) or a wireless interface (such as a IEEE 802.1 1 interface, WiFi ® or a Bluetooth ® interface); and
• a wireline interface for example a bus interface (e.g. USB (or Universal Serial Bus)
• a wide area network interface e.g. USB (or Universal Serial Bus)
• a local area network interface e.g. HDMI (High Definition Multimedia Interface) interface
• a wireless interface such as a IEEE 802.1 1 interface, WiFi ® or a Bluetooth ® interface
• the bitstream F is sent to a destination.
• the bitstream F is stored in a local or remote memory, e.g. a video memory (1 104) or a RAM (1 104), a hard disk (1 103).
• the bitstream is sent to a storage interface (1 105), e.g. an interface with a mass storage, a flash memory, ROM, an optical disc or a magnetic support and/or transmitted over a communication interface (1 1 05), e.g. an interface to a point to point link, a communication bus, a point to multipoint link or a broadcast network.
• the bitstream F is obtained from a source.
• the bitstream is read from a local memory, e.g. a video memory (1 104), a RAM (1004), a ROM (1 103), a flash memory (1 103) or a hard disk (1 1 03).
• the bitstream is received from a storage interface (1 1 05), e.g. an interface with a mass storage, a RAM, a ROM, a flash memory, an optical disc or a magnetic support and/or received from a communication interface (1 105), e.g. an interface to a point to point link, a bus, a point to multipoint link or a broadcast network.
• device 1 100 being configured to implement an encoding method described in relation with Fig. 1 -9, belongs to a set comprising:
• a video server e.g. a broadcast server, a video-on-demand server or a web server.
• device 1 100 being configured to implement a decoding method described in relation with Fig. 10, belongs to a set comprising:
• the device A comprises a processor in relation with memory RAM and ROM which are configured to implement a method for encoding a picture as described in relation with the Fig. 9 and the device B comprises a processor in relation with memory RAM and ROM which are configured to implement a method for decoding as described in relation with Fig. 10.
• Implementations of the various processes and features described herein may be embodied in a variety of different equipment or applications.
• Examples of such equipment include an encoder, a decoder, a post-processor processing output from a decoder, a pre-processor providing input to an encoder, a video coder, a video decoder, a video codec, a web server, a set- top box, a laptop, a personal computer, a cell phone, a PDA, and any other device for processing a picture or a video or other communication devices.
• the equipment may be mobile and even installed in a mobile vehicle.
• a computer readable storage medium can take the form of a computer readable program product embodied in one or more computer readable medium(s) and having computer readable program code embodied thereon that is executable by a computer.
• a computer readable storage medium as used herein is considered a non-transitory storage medium given the inherent capability to store the information therein as well as the inherent capability to provide retrieval of the information therefrom.
• a computer readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. It is to be appreciated that the following, while providing more specific examples of computer readable storage mediums to which the present principles can be applied, is merely an illustrative and not exhaustive listing as is readily appreciated by one of ordinary skill in the art: a portable computer diskette; a hard disk; a read-only memory (ROM); an erasable programmable read-only memory (EPROM or Flash memory); a portable compact disc read-only memory (CD-ROM); an optical storage device; a magnetic storage device; or any suitable combination of the foregoing.
• the instructions may form an application program tangibly embodied on a processor-readable medium.
• Instructions may be, for example, in hardware, firmware, software, or a combination. Instructions may be found in, for example, an operating system, a separate application, or a combination of the two.
• a processor may be characterized, therefore, as, for example, both a device configured to carry out a process and a device that includes a processor-readable medium (such as a storage device) having instructions for carrying out a process. Further, a processor-readable medium may store, in addition to or in lieu of instructions, data values produced by an implementation.
• implementations may produce a variety of signals formatted to carry information that may be, for example, stored or transmitted.
• the information may include, for example, instructions for performing a method, or data produced by one of the described implementations.
• a signal may be formatted to carry as data the rules for writing or reading the syntax of a described example of the present principles, or to carry as data the actual syntax-values written by a described example of the present principles.
• Such a signal may be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal.
• the formatting may include, for example, encoding a data stream and modulating a carrier with the encoded data stream.
• the information that the signal carries may be, for example, analog or digital information.
• the signal may be transmitted over a variety of different wired or wireless links, as is known.
• the signal may be stored on a processor-readable medium.

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