US9270988B2 - Method of determining binary codewords for transform coefficients - Google Patents

Method of determining binary codewords for transform coefficients Download PDF

Info

Publication number
US9270988B2
US9270988B2 US13/671,811 US201213671811A US9270988B2 US 9270988 B2 US9270988 B2 US 9270988B2 US 201213671811 A US201213671811 A US 201213671811A US 9270988 B2 US9270988 B2 US 9270988B2
Authority
US
United States
Prior art keywords
value
symbol
parameter variable
last
threshold
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active - Reinstated, expires
Application number
US13/671,811
Other languages
English (en)
Other versions
US20130114698A1 (en
Inventor
Jian Lou
Xue Fang
Limin Wang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Google Technology Holdings LLC
Original Assignee
Google Technology Holdings LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to BR112014011150-2A priority Critical patent/BR112014011150B1/pt
Application filed by Google Technology Holdings LLC filed Critical Google Technology Holdings LLC
Priority to KR1020147014978A priority patent/KR101660605B1/ko
Priority to CN201280054977.0A priority patent/CN103931197B/zh
Priority to US13/671,811 priority patent/US9270988B2/en
Priority to PCT/US2012/064229 priority patent/WO2013070970A2/fr
Assigned to GENERAL INSTRUMENT CORPORATION reassignment GENERAL INSTRUMENT CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: FANG, XUE, LOU, JIAN, WANG, LIMIN
Publication of US20130114698A1 publication Critical patent/US20130114698A1/en
Assigned to GENERAL INSTRUMENT HOLDINGS, INC. reassignment GENERAL INSTRUMENT HOLDINGS, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GENERAL INSTRUMENT CORPORATION
Assigned to MOTOROLA MOBILITY LLC reassignment MOTOROLA MOBILITY LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GENERAL INSTRUMENT HOLDINGS, INC.
Assigned to Google Technology Holdings LLC reassignment Google Technology Holdings LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MOTOROLA MOBILITY LLC
Publication of US9270988B2 publication Critical patent/US9270988B2/en
Application granted granted Critical
Active - Reinstated legal-status Critical Current
Adjusted expiration legal-status Critical

Links

Images

Classifications

    • H04N19/00296—
    • 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]
    • 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
    • H04N19/10—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
    • H04N19/1887—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 variable length codeword
    • 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
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • 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
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/63—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets
    • H04N19/64—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets characterised by ordering of coefficients or of bits for transmission
    • H04N19/645—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets characterised by ordering of coefficients or of bits for transmission by grouping of coefficients into blocks after the transform
    • 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
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
    • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
    • H03M7/40—Conversion to or from variable length codes, e.g. Shannon-Fano code, Huffman code, Morse code
    • H03M7/4006—Conversion to or from arithmetic code
    • H03M7/4012—Binary arithmetic codes
    • H03M7/4018—Context adapative binary arithmetic codes [CABAC]
    • 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
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding

Definitions

  • the present disclosure relates to the field of video compression, particularly video compression using High Efficiency Video Coding (HEVC) that employ block processing.
  • HEVC High Efficiency Video Coding
  • FIG. 1 depicts a content distribution system 100 comprising a coding system 110 and a decoding system 140 that can be used to transmit and receive HEVC data.
  • the coding system 110 can comprise an input interface 130 , a controller 111 , a counter 112 , a frame memory 113 , an encoding unit 114 , a transmitter buffer 115 and an output interface 135 .
  • the decoding system 140 can comprise a receiver buffer 150 , a decoding unit 151 , a frame memory 152 and a controller 153 .
  • the coding system 110 and the decoding system 140 can be coupled with each other via a transmission path which can carry a compressed bitstream 105 .
  • the controller 111 of the coding system 110 can control the amount of data to be transmitted on the basis of the capacity of the receiver buffer 150 and can include other parameters such as the amount of data per a unit of time.
  • the controller 111 can control the encoding unit 114 to prevent the occurrence of a failure of a received signal decoding operation of the decoding system 140 .
  • the controller 111 can be a processor or include, by way of a non-limiting example, a microcomputer having a processor, a random access memory and a read only memory.
  • Source pictures 120 supplied from, by way of a non-limiting example, a content provider can include a video sequence of frames including source pictures in a video sequence.
  • the source pictures 120 can be uncompressed or compressed. If the source pictures 120 are uncompressed, the coding system 110 can have an encoding function. If the source pictures 120 are compressed, the coding system 110 can have a transcoding function. Coding units can be derived from the source pictures utilizing the controller 111 .
  • the frame memory 113 can have a first area that can be used for storing the incoming frames from the source pictures 120 and a second area that can be used for reading out the frames and outputting them to the encoding unit 114 .
  • the controller 111 can output an area switching control signal 123 to the frame memory 113 .
  • the area switching control signal 123 can indicate whether the first area or the second area is to be utilized.
  • the controller 111 can output an encoding control signal 124 to the encoding unit 114 .
  • the encoding control signal 124 can cause the encoding unit 114 to start an encoding operation, such as preparing the Coding Units based on a source picture.
  • the encoding unit 114 can begin to read out the prepared Coding Units to a high-efficiency encoding process, such as a prediction coding process or a transform coding process which process the prepared Coding Units generating video compression data based on the source pictures associated with the Coding Units.
  • the encoding unit 114 can package the generated video compression data in a packetized elementary stream (PES) including video packets.
  • PES packetized elementary stream
  • the encoding unit 114 can map the video packets into an encoded video signal 122 using control information and a program time stamp (PTS) and the encoded video signal 122 can be transmitted to the transmitter buffer 115 .
  • PTS program time stamp
  • the encoded video signal 122 can be stored in the transmitter buffer 115 .
  • the information amount counter 112 can be incremented to indicate the total amount of data in the transmitter buffer 115 . As data is retrieved and removed from the buffer, the counter 112 can be decremented to reflect the amount of data in the transmitter buffer 115 .
  • the occupied area information signal 126 can be transmitted to the counter 112 to indicate whether data from the encoding unit 114 has been added or removed from the transmitted buffer 115 so the counter 112 can be incremented or decremented.
  • the controller 111 can control the production of video packets produced by the encoding unit 114 on the basis of the occupied area information 126 which can be communicated in order to anticipate, avoid, prevent, and/or detect an overflow or underflow from taking place in the transmitter buffer 115 .
  • the information amount counter 112 can be reset in response to a preset signal 128 generated and output by the controller 111 . After the information counter 112 is reset, it can count data output by the encoding unit 114 and obtain the amount of video compression data and/or video packets which have been generated. The information amount counter 112 can supply the controller 111 with an information amount signal 129 representative of the obtained amount of information. The controller 111 can control the encoding unit 114 so that there is no overflow at the transmitter buffer 115 .
  • the decoding system 140 can comprise an input interface 170 , a receiver buffer 150 , a controller 153 , a frame memory 152 , a decoding unit 151 and an output interface 175 .
  • the receiver buffer 150 of the decoding system 140 can temporarily store the compressed bitstream 105 , including the received video compression data and video packets based on the source pictures from the source pictures 120 .
  • the decoding system 140 can read the control information and presentation time stamp information associated with video packets in the received data and output a frame number signal 163 which can be applied to the controller 153 .
  • the controller 153 can supervise the counted number of frames at a predetermined interval. By way of a non-limiting example, the controller 153 can supervise the counted number of frames each time the decoding unit 151 completes a decoding operation.
  • the controller 153 can output a decoding start signal 164 to the decoding unit 151 .
  • the controller 153 can wait for the occurrence of a situation in which the counted number of frames becomes equal to the predetermined amount.
  • the controller 153 can output the decoding start signal 164 when the situation occurs.
  • the controller 153 can output the decoding start signal 164 when the frame number signal 163 indicates the receiver buffer 150 is at the predetermined capacity.
  • the encoded video packets and video compression data can be decoded in a monotonic order (i.e., increasing or decreasing) based on presentation time stamps associated with the encoded video packets.
  • the decoding unit 151 can decode data amounting to one picture associated with a frame and compressed video data associated with the picture associated with video packets from the receiver buffer 150 .
  • the decoding unit 151 can write a decoded video signal 162 into the frame memory 152 .
  • the frame memory 152 can have a first area into which the decoded video signal is written, and a second area used for reading out decoded pictures 160 to the output interface 175 .
  • the coding system 110 can be incorporated or otherwise associated with a transcoder or an encoding apparatus at a headend and the decoding system 140 can be incorporated or otherwise associated with a downstream device, such as a mobile device, a set top box or a transcoder.
  • the coding system 110 and decoding system 140 can be utilized separately or together to encode and decode video data according to various coding formats, including High Efficiency Video Coding (HEVC).
  • HEVC is a block based hybrid spatial and temporal predictive coding scheme.
  • input images such as video frames, can be divided into square blocks called Largest Coding Units (LCUs) 200 , as shown in FIG. 2 .
  • LCUs 200 can each be as large as 128 ⁇ 128 pixels, unlike other coding schemes that break input images into macroblocks of 16 ⁇ 16 pixels.
  • each LCU 200 can be partitioned by splitting the LCU 200 into four Coding Units (CUs) 202 .
  • CUs Coding Units
  • CUs 202 can be square blocks each a quarter size of the LCU 200 . Each CU 202 can be further split into four smaller CUs 202 each a quarter size of the larger CU 202 . By way of a non-limiting example, the CU 202 in the upper right corner of the LCU 200 depicted in FIG. 3 can be divided into four smaller CUs 202 . In some embodiments, these smaller CUs 202 can be further split into even smaller sized quarters, and this process of splitting CUs 202 into smaller CUs 202 can be completed multiple times.
  • the present invention provides an improved system for HEVC.
  • a method of determining binary codewords for transform coefficients in an efficient manner is provided.
  • Codewords for the transform coefficients within transform units (TUs) that are subdivisions of the CUs 202 are used in encoding input images and/or macroblocks.
  • a method comprises providing a transform unit including one or more subsets of transform coefficients, each transform coefficient having a quantized value, determining a symbol for each transform coefficient having a quantized value equal to or greater than a threshold value by subtracting the threshold value from the quantized value of the transform coefficient, providing a parameter variable set to an initial value of zero, converting each symbol into a binary codeword based on the current value of the parameter variable and the value of the symbol, and updating the value of the parameter variable with a new current value after each symbol has been converted, the new current value being based at least in part on the last value of the parameter variable and the value of the last converted symbol in the current or previous subset.
  • the invention includes a method of determining binary codewords for transform coefficients that uses a look up table to determine the transform coefficients.
  • the method comprises providing a transform unit comprising one or more subsets of transform coefficients, each transform coefficient having a quantized value, determining a symbol for each transform coefficient having a quantized value equal to or greater than a threshold value, by subtracting the threshold value from the quantized value of the transform coefficient, providing a parameter variable set to an initial value of zero, converting each symbol into a binary codeword based on the current value of the parameter variable and the value of the symbol, looking up a new current value from a table based on the last value of the parameter variable and the value of the last converted symbol, and replacing the value of the parameter variable with the new current value.
  • the invention includes a method of determining binary codewords for transform coefficients that uses one or more mathematical conditions that can be performed using logic rather than requiring a look up table.
  • the method comprises providing a transform unit comprising one or more subsets of transform coefficients, each transform coefficient having a quantized value, determining a symbol for each transform coefficient having a quantized value equal to or greater than a threshold value, by subtracting the threshold value from the quantized value of the transform coefficient, providing a parameter variable set to an initial value of zero, converting each symbol into a binary codeword based on the current value of the parameter variable and the value of the symbol, determining whether the last value of the parameter variable and the value of the last converted symbol together satisfy one or more conditions, and mathematically adding an integer of one to the last value of the parameter variable for each of the one or more conditions that is satisfied.
  • FIG. 1 depicts an embodiment of a content distribution system.
  • FIG. 2 depicts an embodiment of an input image divided into Large Coding Units.
  • FIG. 3 depicts an embodiment of a Large Coding Unit divided into Coding Units.
  • FIG. 4 depicts a quadtree representation of a Large Coding Unit divided into Coding Units.
  • FIG. 5 depicts possible exemplary arrangements of Prediction Units within a Coding Unit.
  • FIG. 6 depicts a block diagram of an embodiment of a method for encoding and/or decoding a Prediction Unit.
  • FIG. 7 depicts an exemplary embodiment of a Coding Unit divided into Prediction Units and Transform Units.
  • FIG. 8 depicts an exemplary embodiment of a quadtree representation of a Coding Unit divided into Transform Units.
  • FIG. 9 depicts an embodiment of a method of performing context-based adaptive binary arithmetic coding.
  • FIG. 10 depicts an exemplary embodiment of a significance map.
  • FIG. 11 depicts an embodiment of a reverse zig-zag scan of transform coefficients within a Transform Unit and subsets of transform coefficients.
  • FIG. 12 depicts an embodiment of a method of obtaining coefficient levels and symbols for transform coefficients.
  • FIG. 13 depicts an embodiment of the scanning order of transform coefficients within subsets.
  • FIG. 14 depicts exemplary embodiments of maximum symbol values for associated parameter variables.
  • FIG. 15 depicts an exemplary embodiment of a table for converting symbols into binary codewords based on parameter variables.
  • FIG. 16 depicts an embodiment of a method for coding symbols and updating parameter variables.
  • FIG. 17 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 4, 13, 11, and 10.
  • FIG. 18 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 3, 6, and 12.
  • FIG. 19 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 5, and 11.
  • FIG. 20 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 2, 4, 13, 11, and 10.
  • FIG. 21 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 3, 6, and 12.
  • FIG. 22 depicts exemplary code that can be used to update the parameter variable based on conditional symbol thresholds of 2, 5, and 11.
  • FIG. 23 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of A, B, and C.
  • FIG. 24 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of A, B, and C.
  • FIG. 25 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 4, and 12.
  • FIG. 26 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 2, 4, and 12.
  • FIG. 27 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 4, and 13.
  • FIG. 28 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 2, 4, and 13.
  • FIG. 29 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 4, and 11.
  • FIG. 30 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 2, 4, and 11.
  • FIG. 31 depicts an exemplary embodiment of a low complexity updating table with conditional symbol thresholds of 2, 4, and 10.
  • FIG. 32 depicts an exemplary embodiment of a combination logic representation of conditions for conditional symbol thresholds of 2, 4, and 10.
  • FIG. 33 depicts an exemplary embodiment of computer hardware.
  • an input image such as a video frame
  • CUs that are then identified in code.
  • the CUs are then further broken into sub-units that are coded as will be described subsequently.
  • a quadtree data representation can be used to describe the partition of a LCU 200 .
  • the quadtree representation can have nodes corresponding to the LCU 200 and CUs 202 .
  • a flag “1” can be assigned if the LCU 200 or CU 202 is split into four CUs 202 . If the node is not split into CUs 202 , a flag “0” can be assigned.
  • the quadtree representation shown in FIG. 4 can describe the LCU partition shown in FIG. 3 , in which the LCU 200 is split into four CUs 202 , and the second CU 202 is split into four smaller CUs 202 .
  • the binary data representation of the quadtree can be a CU split flag that can be coded and transmitted as overhead, along with other data such as a skip mode flag, merge mode flag, and the PU coding mode described subsequently.
  • the CU split flag quadtree representation shown in FIG. 4 can be coded as the binary data representation “10100.”
  • the final CUs 202 can be broken up into one or more blocks called prediction units (PUs) 204 .
  • PUs 204 can be square or rectangular.
  • a CU 202 with dimensions of 2N ⁇ 2N can have one of the four exemplary arrangements of PUs 204 shown in FIG. 5 , with PUs 204 having dimensions of 2N ⁇ 2N, 2N ⁇ N, N ⁇ 2N, or N ⁇ N.
  • a PU can be obtained through spatial or temporal prediction. Temporal prediction is related to inter mode pictures. Spatial prediction relates to intra mode pictures. The PUs 204 of each CU 202 can, thus, be coded in either intra mode or inter mode. Features of coding relating to intra mode and inter mode pictures is described in the paragraphs to follow.
  • Intra mode coding can use data from the current input image, without referring to other images, to code an I picture.
  • the PUs 204 can be spatially predictive coded.
  • Each PU 204 of a CU 202 can have its own spatial prediction direction.
  • Spatial prediction directions can be horizontal, vertical, 45-degree diagonal, 135 degree diagonal, DC, planar, or any other direction.
  • the spatial prediction direction for the PU 204 can be coded as a syntax element.
  • brightness information (Luma) and color information (Chroma) for the PU 204 can be predicted separately.
  • the number of Luma intra prediction modes for 4 ⁇ 4, 8 ⁇ 8, 16 ⁇ 16, 32 ⁇ 32, and 64 ⁇ 64 blocks can be 18, 35, 35, 35, and 4 respectively.
  • the number of Luma intra prediction modes for blocks of any size can be 35.
  • An additional mode can used for the Chroma intra prediction mode.
  • the Chroma prediction mode can be called “IntraFromLuma.”
  • Inter mode coding can use data from the current input image and one or more reference images to code “P” pictures and/or “B” pictures. In some situations and/or embodiments, inter mode coding can result in higher compression than intra mode coding.
  • inter mode PUs 204 can be temporally predictive coded, such that each PU 204 of the CU 202 can have one or more motion vectors and one or more associated reference images. Temporal prediction can be performed through a motion estimation operation that searches for a best match prediction for the PU 204 over the associated reference images. The best match prediction can be described by the motion vectors and associated reference images.
  • P pictures use data from the current input image and one or more previous reference images.
  • B pictures use data from the current input image and both previous and subsequent reference images, and can have up to two motion vectors.
  • the motion vectors and reference pictures can be coded in the HEVC bitstream.
  • the motion vectors can be coded as syntax elements “MV,” and the reference pictures can be coded as syntax elements “refIdx.”
  • inter mode coding can allow both spatial and temporal predictive coding.
  • FIG. 6 depicts a block diagram of how a PU 204 , x, can be encoded and/or decoded.
  • a predicted PU 206 , x′ that is predicted by intra mode at 602 or inter mode at 604 , as described above, can be subtracted from the current PU 204 , x, to obtain a residual PU 208 , e.
  • the residual PU 208 , e can be transformed with a block transform into one or more transform units (TUs) 210 , E.
  • Each TU 210 can comprise one or more transform coefficients 212 .
  • the block transform can be square. In alternate embodiments, the block transform can be non-square.
  • a set of block transforms of different sizes can be performed on a CU 202 , such that some PUs 204 can be divided into smaller TUs 210 and other PUs 204 can have TUs 210 the same size as the PU 204 .
  • Division of CUs 202 and PUs 204 into TUs 210 can be shown by a quadtree representation.
  • the quadtree representation shown in FIG. 8 depicts the arrangement of TUs 210 within the CU 202 shown in FIG. 7 .
  • the transform coefficients 212 of the TU 210 , E can be quantized into one of a finite number of possible values. In some embodiments, this is a lossy operation in which data lost by quantization may not be recoverable.
  • the quantized transform coefficients 212 can be entropy coded, as discussed below, to obtain the final compression bits 214 .
  • the quantized transform coefficients 212 can be dequantized into dequantized transform coefficients 216 E′.
  • the dequantized transform coefficients 216 E′ can then be inverse transformed to reconstruct the residual PU 218 , e′.
  • the reconstructed residual PU 218 , e′ can then be added to a corresponding prediction PU 206 , x′, obtained through either spatial prediction at 602 or temporal prediction at 604 , to obtain a reconstructed PU 220 , x′′.
  • a deblocking filter can be used on reconstructed PUs 220 , x′′, to reduce blocking artifacts.
  • a sample adaptive offset process is also provided that can be conditionally performed to compensate the pixel value offset between reconstructed pixels and original pixels. Further, at 620 , an adaptive loop filter can be conditionally used on the reconstructed PUs 220 , x′′, to reduce or minimize coding distortion between input and output images.
  • the reconstructed image is a reference image that will be used for future temporal prediction in inter mode coding
  • the reconstructed images can be stored in a reference buffer 622 .
  • Intra mode coded images can be a possible point where decoding can begin without needing additional reconstructed images.
  • HEVC can use entropy coding schemes during step 612 such as context-based adaptive binary arithmetic coding (CABAC).
  • CABAC context-based adaptive binary arithmetic coding
  • FIG. 9 The coding process for CABAC is shown in FIG. 9 .
  • the position of the last significant transform coefficient of the transform units 210 can be coded.
  • the quantized transform coefficients are created by quantizing the TUs 210 .
  • Transform coefficients 212 can be significant or insignificant.
  • FIG. 10 shows a significance map 1002 of the transform coefficients 212 . Insignificant transform coefficients 212 can have a quantized value of zero, while significant transform coefficients 212 can have a quantized value of one or more.
  • significant transform coefficients 212 can also be known as non-zero quantized transform coefficients 212 . If a TU 210 comprises one or more significant transform coefficients 212 , the coordinates of the last significant transform coefficient 212 along a forward zig-zag coding scan from the top left corner of the TU 210 to the lower right corner of the TU 210 , as shown in FIG. 10 , can be coded. In alternate embodiments, the significant transform coefficients 212 can be scanned along an inverse wavefront scan, inverse horizontal scan, inverse vertical scan, or any other scan order.
  • FIG. 10 depicts the position of the last significant transform 212 b within a TU 210 which is being coded in block 902 of FIG. 9 .
  • the significance map 1002 can be coded to indicate the positions of each of the significant transform coefficients 212 in the TU 210 .
  • a significance map 1002 can comprise a binary element for each position in the TU 210 .
  • the binary element can be coded as “0” to indicate that the transform coefficient 212 at that position is not significant.
  • the binary element can be coded as “1” to indicate that the transform coefficient 212 at that position is significant.
  • FIG. 11 illustrates how the quantized transform coefficients 212 of the TUs 210 can be divided into groups.
  • the groups can be sub-blocks.
  • Sub-blocks can be square blocks of 16 quantized transform coefficients 212 .
  • the groups can be subsets 1102 .
  • Subsets 1102 can comprise 16 quantized transform coefficients 212 that are consecutive along the scan order of a backwards zig-zag scan, as shown in FIG. 11 .
  • the first subset can be the subset 1102 that includes the last significant transform coefficient 212 b , regardless of where the last significant transform coefficient 212 b is within the subset.
  • the last significant transform coefficient 212 b can be the 14th transform coefficient 212 in the subset, followed by two insignificant transform coefficients.
  • the first subset can be the subset 1102 containing the last significant transform coefficient 212 b , and any groups before the first subset 1102 are not considered part of a subset 1102 .
  • FIG. 1 By way of a non-limiting example, in FIG. 1
  • the first subset 1102 “Subset 0” is the second grouping of 16 transform coefficients 212 along the reverse zig-zap scan order, while the group of 16 transform coefficients 212 at the lower right corner of the TU 210 are not part of a subset 1102 because none of those transform coefficients 212 are significant.
  • the first subset 1102 can be denoted as “subset 0,” and additional subsets 1102 can be denoted as “subset 1,” “subset 2,” up to “subset N.”
  • the last subset 1102 can be the subset 1102 with the DC transform coefficient 212 at position 0, 0 at the upper left corner of the TU 210 .
  • each quantized transform coefficient 212 can be coded into binary values to obtain final compression bits 214 shown in FIG. 6 , including coding for significant coefficient levels.
  • the absolute value of each quantized transform coefficient 212 can be coded separately from the sign of the quantized transform coefficient 212 .
  • FIG. 12 illustrates coding steps that deal with taking an absolute value of the quantized transform coefficients. As shown in FIG. 12 , at 1202 the absolute value of each quantized transform coefficient 212 can be taken to enable obtaining the coefficient level 222 for that quantized transform coefficient 212 at block 1204 .
  • the coefficient levels 222 obtained at block 1204 that are expected to occur with a higher frequency can be coded before coefficient levels 222 that are expected to occur with lower frequencies.
  • coefficient levels 222 of 0, 1, or 2 can be expected to occur most frequently. Coding the coefficient levels 222 in three parts can identify the most frequently occurring coefficient levels 222 , leaving more complex calculations for the coefficient levels 222 that can be expected to occur less frequently. In some embodiments, this can be done by coding the coefficient levels 222 in three parts.
  • the coefficient level 222 of a quantized transform coefficient 212 can be checked to determine whether it is greater than one. If the coefficient level 222 is greater than one, the coefficient level 222 can be checked to determine whether it is greater than two.
  • the coefficient level 222 can be subtracted by a threshold value 224 of three to obtain a symbol.
  • the coefficient level 222 can be coded as three variables: “coeff_abs_level_greater1_flag,” “coeff_abs_level_greater2_flag,” and “coeff_abs_level_minus3.”
  • “coeff_abs_level_greater1_flag” can be set to “1.” If “coeff_abs_level_greater1_flag” is set to “1” and the quantized transform coefficient 212 also has a coefficient level 222 of three or more, “coeff_abs_level_greater2_flag” can be set to “1.” If “coeff_abs_level_greater2_flag” is set to “1.”
  • the quantized transform coefficient's symbol 226 can be converted to a binary codeword 228 that can be part of the final compression bits 214 generated as shown in FIG. 6 .
  • FIG. 13 illustrates how each symbol 226 can be coded by scanning through each subset 1102 and converting each symbol 226 of the subset 1102 in order according to the value of the parameter variable 230 , and then moving to the symbols 226 of the next subset 1102 .
  • the conversion to a binary codeword 228 can be performed with Truncated Rice code alone, or with a combination of Truncated Rice code and 0th order exponential-Golomb (Exp-Golomb) code.
  • the Truncated Rice code can obtain a binary codeword 228 based a parameter variable 230 and the symbol 226 .
  • a diagram showing this coding progression is shown in FIG. 13 for the subsets 0 and 1 along the zig-zag lines of FIG. 11 .
  • the current scanning position can be denoted by “n.”
  • the parameter variable 230 can be a global variable that can be updated as each symbol 226 is coded.
  • the parameter variable 230 can control the flatness of the codeword distribution.
  • the parameter variable 230 can be any integer between 0 and N.
  • N can be 3, such that the parameter variable 230 can be 0, 1, 2, or 3.
  • the parameter variable 230 can be denoted as “cRiceParam” as illustrated in FIG. 15 as well as FIG. 14 .
  • each parameter variable 230 can have an associated maximum symbol value 232 that denotes the truncation point for the Truncated Rice code.
  • the maximum symbol value 232 for a particular parameter variable 230 can be denoted as “cTRMax” 232 as illustrated in FIG. 14 which depicts an exemplary table of maximum symbol values 232 “cTRMax” for parameter variables 230 “cRiceParam.”
  • the table of FIG. 14 is labeled as Table 1, as it provides a first listing cRiceParam values 230 relative to maximum value symbols cTRMax 232 . If the symbol 226 of FIG.
  • FIG. 15 depicts an exemplary table of binary codewords 228 generated based on symbols 226 and parameter variables 230 . Since FIG. 15 provides a second table listing cRiceParam parameter variables 230 relative to other values, it is labeled as Table 2.
  • converting the symbol 226 according to Truncated Rice code with a lower parameter variable 230 can result in a binary codeword 228 having fewer bits than converting the same symbol 226 according to Truncated Rice code with a higher parameter variable 230 .
  • using a parameter variable 230 of 0 to convert a symbol 226 of 0 can result in the binary codeword 228 of “0” having 1 bit, while using the parameter variable 230 of 1 to convert the symbol 226 of 0 can result in the binary codeword 228 of “00” having 2 bits.
  • converting the symbol 226 according to Truncated Rice code with a higher parameter variable 230 can result in a binary codeword 228 having fewer bits than converting the same symbol 226 according to Truncated Rice code with a lower parameter variable 230 .
  • using a parameter variable 230 of 0 to convert a symbol 226 of 6 can result in the binary codeword 228 of “1111110” having 7 bits, while using the parameter variable 230 of 2 to convert the symbol 226 of 6 can result in the binary codeword 228 of “1010” having 4 bits.
  • FIG. 16 is a flow chart depicting a method for entropy coding the symbols 226 .
  • the parameter variable 230 can be initially set to a value of zero.
  • the coding system 110 can move to the next symbol 226 .
  • the next symbol 226 can be the first symbol 226 in the first subset 1102 as illustrated in FIG. 11 .
  • the symbol 226 can be coded with Truncated Rice and/or Exp-Golomb code using the current value of the parameter variable 230 .
  • the parameter variable 230 can be updated based on the last value of the parameter variable 230 and the value of the last symbol 226 that was coded.
  • the updated value of the parameter variable 230 can be the same as the last value of the parameter variable 230 . In other situations and/or embodiments, the updated value of the parameter variable 230 can be greater than the last value of the parameter variable 230 .
  • the parameter variable 230 can be updated based upon calculations or upon values derived from a table as described herein subsequently.
  • the coding system 110 can return to 1604 and move to the next symbol 226 .
  • the next symbol 226 can be in the current subset 1102 or in the next subset 1102 .
  • the next symbol 226 can then be coded at 1606 using the updated value of the parameter variable 230 and the process can repeat for all remaining symbols 226 in the TU 210 .
  • the parameter variable 230 can be updated based on the last value of the parameter variable 230 from the previous subset 1102 , such that the parameter variable 230 is not reset to zero at the first symbol 226 of each subset 1102 .
  • the parameter variable 230 can be set to zero at the first symbol 226 of each subset 1102 .
  • Truncated Rice code with a smaller cRiceParam parameter value 230 can be preferred to code the symbols with smaller codewords, as they need fewer bits to represent. For example, if a symbol 226 has a value of 0, using Truncated Rice code with a cRiceParam parameter value 230 equal to 0, only 1 bit is needed, but 2, 3, or 4 bits are needed when the cRiceParam value is 2, 3, or 4, respectively. If a symbol has a value of 6, using Truncated Rice code with a cRiceParam value equal to 0, 7 bits are needed. But 5, 4, or 4 bits are needed when the cRiceParam value is 2, 3, or 4, respectively.
  • the cRiceParam 230 labeled with a variable coeff_level_minus3[n] is derived and updated based on a table as follows. For a TU subset, the cRiceParam 230 is initially set to 0, and is then updated based on the previous cRiceParam and the coeff_abs_level_minus3[n ⁇ 1] according to the table of FIG. 17 . Because FIG. 17 shows a third table listing symbol values 226 relative to cRiceParam parameter values 230 , the table is labeled as Table 3. Subsequent tables showing a similar comparison will, likewise, be labeled consecutively.
  • cRiceParam 230 is reset once per subset with initial “0” values.
  • the cRiceParam calculation for coeff_abs_level_minus3 can be reset to 0 for each subset, which favors smaller symbol value coding.
  • the absolute values of the non-zero quantized transform coefficients tend to get larger and larger. Therefore, resetting cRiceParam to 0 for each subset might not give optimal compression performance.
  • each circle stands for a quantized transform coefficient and the number inside each circle is the value of coeff_abs_level_minus3. If it is “NA”, it means there is no syntax of coeff_abs_level_minus3 for that coefficient.
  • the values of coeff_abs_level_minus3 tend to get larger within each subset and also from subset to subset, as shown in the example of FIG. 13 .
  • cRiceParam is set to 2 for “5” in subset 0, and with cRiceParam set to 2, the value of “5” is binarized into a codeword of “1001”, or 4 bits, as shown in Table 2 of FIG. 15 .
  • cRiceParam is then reset to 0 in subset 1. Now, with the reset cRiceParam of 0, the same value of “5” in subset 1 is now binarized into a codeword of 111110, or 6 bits, as shown in Table 2. Clearly, this resetting process not only introduces additional checking operations, but also can possibly result in inferior coding performance.
  • the cRiceParam parameters 230 are derived as follows. First, for a TU, cRiceParam is initially set to 0, and is then updated based on the previous cRiceParam and coeff_abs_level_minus3[n ⁇ 1] according to a cRiceParam update table, such as Tables 4 and 5. In these embodiments, cRiceParam is only reset once per TU, and not per subset of a TU as indicated with respect to the embodiment using Table 3.
  • Table 5 of FIG. 19 is generated from Table 2 of FIG. 15 by analyzing the number of bits needed for each symbol 226 with a different cRiceParam value 230 while assuming the next level value is statistically no smaller than the current level along a reverse scan. For example, if the current symbol 226 is 2 and the cRiceParam is 0, the chance that the next symbol is larger than 2 is high and applying Truncated Rice code with cRiceParam equal to 1 might reduce the number of bits. If the current symbol is 5 and cRiceParam is 1, the chance that the next symbol is larger than 5 is high and applying Truncated Rice code with cRiceParam equal to 2 might reduce the number of bits. If the current symbol is 11 and the cRiceParam is 2, the chance that the next symbol is larger than 11 is high and applying Truncated Rice code with cRiceParam equal to 3 might reduce the number of bits.
  • updating the parameter variable 230 at 1608 can be determined from a comparison equation rather than a table. In the comparison, it is determined whether both the last value of the parameter variable 230 and the value of the last coded symbol 226 meet one or more conditions 1702 , as illustrated in FIG. 20 .
  • the value of the last coded symbol 226 can be denoted as “coeff_abs_level_minus3[n ⁇ 1]” as it was in Tables 3-5.
  • the parameter variable 230 can be updated depending on which conditions 1702 are met, and the value of the current symbol 226 can then be coded based on the updated parameter variable 230 using Truncated Rice code and/or Exp-Golomb Code.
  • each condition 1702 can comprise two parts, a conditional symbol threshold and a conditional parameter threshold. In these embodiments, the condition 1702 can be met if the value of the symbol 226 is equal to greater than the conditional symbol threshold and the parameter variable 230 is equal to or greater than the conditional parameter threshold. In alternate embodiments, each condition 1702 can have any number of parts or have any type of condition for either or both the symbol 226 and parameter variable 230 .
  • combination logics can perform the comparison in place of an updating table as the logic can use very few processor cycles.
  • FIG. 20 An example of the combination logic that determines the cRiceParam for updating in the place of Table 3 is shown in FIG. 20 .
  • FIG. 21 An example of combination logic for representing Table 4 is shown in FIG. 21 .
  • FIG. 22 An example of combination logic for representing Table 5 is shown in FIG. 22 .
  • the possible outcomes of the conditions 1702 based on possible values of the parameter variable 230 and the last coded symbols 226 can be stored in memory as a low complexity update table 1704 as illustrated in the table of FIG. 17 as well as other subsequent figures.
  • the parameter variable 230 can be updated by performing a table lookup from the low complexity update table 1704 based on the last value of the parameter variable 230 and the value of the last coded symbol 226 .
  • a low complexity level parameter updating table in CABAC can be provided that in some embodiments can operate more efficiently than previous tables and not require the logic illustrated in FIGS. 20-22 .
  • these low complexity level parameter updating tables the following applies: (1) Inputs: Previous cRiceParam and coeff_abs_level_minus3[n ⁇ 1]. (2) Outputs: cRiceParam. (3) Previous cRiceParam and cRiceParam could have a value of 0, 1, 2 or 3.
  • the parameter variable 230 can: remain the same when the value of the last coded symbol 226 is between 0 and A ⁇ 1; (2) The parameter variable 230 can be set to one or remain at the last value of the parameter variable 230 , whichever is greater, when the symbol 226 is between A and B ⁇ 1; (3) The parameter variable 230 can be set to two or remain at the last value of the parameter variable 230 , whichever is greater, when the symbol 226 is between B and C ⁇ 1; or (4) The parameter variable 230 can be set to three when the symbol 226 is greater than C ⁇ 1.
  • the low complexity update table 1704 labeled Table 6, for these conditions 1702 is depicted in FIG. 23 .
  • A, B, and C can be set to any desired values.
  • A, B, or C can be the conditional symbol threshold respectively, and the value of 0, 1, or 2 can be the parameter symbol threshold respectively.
  • FIGS. 19-31 A selection of non-limiting examples of update tables 1704 and their associated combination logic representations 1706 with particular values of A, B, and C, are depicted in FIGS. 19-31 .
  • FIGS. 19 and 20 respectively depict an update table 1704 and combination logic representation for conditional symbol thresholds of 3, 6, and 13.
  • FIGS. 29 and 30 respectively depict an update table 9 and combination logic representation for conditional symbol thresholds of 2, 4, and 11.
  • FIGS. 31 and 32 respectively depict an update table 10 and combination logic representation for conditional symbol thresholds of 2, 4, and 10.
  • execution of the sequences of instructions required to practice the embodiments may be performed by a computer system 3300 as shown in FIG. 20 .
  • execution of the sequences of instructions is performed by a single computer system 3300 .
  • two or more computer systems 3300 coupled by a communication link 3315 may perform the sequence of instructions in coordination with one another.
  • a description of only one computer system 3300 may be presented herein, it should be understood that any number of computer systems 3300 may be employed.
  • FIG. 20 is a block diagram of the functional components of a computer system 3300 .
  • the term computer system 3300 is broadly used to describe any computing device that can store and independently run one or more programs.
  • the computer system 3300 may include a communication interface 3314 coupled to the bus 3306 .
  • the communication interface 3314 provides two-way communication between computer systems 3300 .
  • the communication interface 3314 of a respective computer system 3300 transmits and receives electrical, electromagnetic or optical signals that include data streams representing various types of signal information, e.g., instructions, messages and data.
  • a communication link 3315 links one computer system 3300 with another computer system 3300 .
  • the communication link 3315 may be a LAN, an integrated services digital network (ISDN) card, a modem, or the Internet.
  • ISDN integrated services digital network
  • a computer system 3300 may transmit and receive messages, data, and instructions, including programs, i.e., application, code, through its respective communication link 3315 and communication interface 3314 .
  • Received program code may be executed by the respective processor(s) 3307 as it is received, and/or stored in the storage device 3310 , or other associated non-volatile media, for later execution.
  • the computer system 3300 operates in conjunction with a data storage system 3331 , e.g., a data storage system 3331 that contains a database 3332 that is readily accessible by the computer system 3300 .
  • the computer system 3300 communicates with the data storage system 3331 through a data interface 3333 .
  • Computer system 3300 can include a bus 3306 or other communication mechanism for communicating the instructions, messages and data, collectively, information, and one or more processors 3307 coupled with the bus 3306 for processing information.
  • Computer system 3300 also includes a main memory 3308 , such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 3306 for storing dynamic data and instructions to be executed by the processor(s) 3307 .
  • the computer system 3300 may further include a read only memory (ROM) 3309 or other static storage device coupled to the bus 3306 for storing static data and instructions for the processor(s) 3307 .
  • a storage device 3310 such as a magnetic disk or optical disk, may also be provided and coupled to the bus 3306 for storing data and instructions for the processor(s) 3307 .
  • a computer system 3300 may be coupled via the bus 3306 to a display device 3311 , such as an LCD screen.
  • a display device 3311 such as an LCD screen.
  • An input device 3312 e.g., alphanumeric and other keys, is coupled to the bus 3306 for communicating information and command selections to the processor(s) 3307 .
  • an individual computer system 3300 performs specific operations by their respective processor(s) 3307 executing one or more sequences of one or more instructions contained in the main memory 3308 .
  • Such instructions may be read into the main memory 3308 from another computer-usable medium, such as the ROM 3309 or the storage device 3310 .
  • Execution of the sequences of instructions contained in the main memory 3308 causes the processor(s) 3307 to perform the processes described herein.
  • hard-wired circuitry may be used in place of or in combination with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and/or software.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
US13/671,811 2011-11-08 2012-11-08 Method of determining binary codewords for transform coefficients Active - Reinstated 2034-04-20 US9270988B2 (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
KR1020147014978A KR101660605B1 (ko) 2011-11-08 2012-11-08 변환 계수들에 대한 이진 코드워드들을 결정하는 방법
CN201280054977.0A CN103931197B (zh) 2011-11-08 2012-11-08 确定用于变换系数的二进制码字的方法
US13/671,811 US9270988B2 (en) 2011-11-08 2012-11-08 Method of determining binary codewords for transform coefficients
PCT/US2012/064229 WO2013070970A2 (fr) 2011-11-08 2012-11-08 Procédé de détermination de mots codés binaires pour des coefficients de transformée
BR112014011150-2A BR112014011150B1 (pt) 2011-11-08 2012-11-08 Método de determinação de palavras de código binárias para coeficientes de transformada

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US201161556826P 2011-11-08 2011-11-08
US201161563774P 2011-11-26 2011-11-26
US201161564248P 2011-11-28 2011-11-28
US13/671,811 US9270988B2 (en) 2011-11-08 2012-11-08 Method of determining binary codewords for transform coefficients

Publications (2)

Publication Number Publication Date
US20130114698A1 US20130114698A1 (en) 2013-05-09
US9270988B2 true US9270988B2 (en) 2016-02-23

Family

ID=48223685

Family Applications (1)

Application Number Title Priority Date Filing Date
US13/671,811 Active - Reinstated 2034-04-20 US9270988B2 (en) 2011-11-08 2012-11-08 Method of determining binary codewords for transform coefficients

Country Status (6)

Country Link
US (1) US9270988B2 (fr)
EP (1) EP2777268A2 (fr)
KR (1) KR101660605B1 (fr)
CN (1) CN103931197B (fr)
BR (1) BR112014011150B1 (fr)
WO (1) WO2013070970A2 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200244962A1 (en) * 2015-06-09 2020-07-30 Microsoft Technology Licensing, Llc Robust encoding/decoding of escape-coded pixels in palette mode
US20200267403A1 (en) * 2016-06-29 2020-08-20 Interdigital Vc Holdings, Inc. Method and apparatus for improved significance flag coding using simple local predictor
US11758162B2 (en) 2014-09-30 2023-09-12 Microsoft Technology Licensing, Llc Rules for intra-picture prediction modes when wavefront parallel processing is enabled
US12096024B2 (en) 2013-10-14 2024-09-17 Microsoft Technology Licensing, Llc Features of base color index map mode for video and image coding and decoding

Families Citing this family (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
BR112014011155B1 (pt) 2011-11-08 2023-04-04 Google Technology Holdings LLC Método de determinação de uma palavra de código binária para um símbolo, codificador de vídeo e meio que pode ser lido em computador
US9172962B2 (en) * 2012-01-20 2015-10-27 Blackberry Limited Methods and systems for pipelining within binary arithmetic coding and decoding
WO2013109993A1 (fr) 2012-01-21 2013-07-25 General Instrument Corporation Procédé de détermination de mots de code binaires pour des coefficients de transformée
CN105027560A (zh) 2012-01-21 2015-11-04 摩托罗拉移动有限责任公司 确定用于变换系数的二进制码字的方法
US9479780B2 (en) 2012-02-01 2016-10-25 Google Technology Holdings LLC Simplification of significance map coding
US9565435B2 (en) 2012-02-04 2017-02-07 Google Technology Holdings LLC Devices and methods for context reduction in last significant coefficient position coding
US9167245B2 (en) 2012-02-05 2015-10-20 Google Technology Holdings LLC Method of determining binary codewords for transform coefficients
US9332257B2 (en) 2012-10-01 2016-05-03 Qualcomm Incorporated Coded black flag coding for 4:2:2 sample format in video coding
US10021419B2 (en) * 2013-07-12 2018-07-10 Qualcomm Incorported Rice parameter initialization for coefficient level coding in video coding process
US9781424B2 (en) 2015-01-19 2017-10-03 Google Inc. Efficient context handling in arithmetic coding
WO2018023554A1 (fr) * 2016-08-04 2018-02-08 SZ DJI Technology Co., Ltd. Système et procédés de régulation de débit binaire
KR102629474B1 (ko) * 2018-05-09 2024-01-26 삼성전자주식회사 데이터 압축 및 복원을 위한 전자 장치 및 그 압축 방법
BR112021004516B1 (pt) * 2018-09-11 2021-12-14 Lg Electronics Inc Método de decodificação de imagem executado por um aparelho de decodificação, método de codificação de imagem executado por um aparelho de codificação e mídia de armazenamento legível por computador

Citations (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6014095A (en) 1996-12-27 2000-01-11 Nec Corporation Variable length encoding system
US20050123207A1 (en) 2003-12-04 2005-06-09 Detlev Marpe Video frame or picture encoding and decoding
US20060103556A1 (en) 2004-10-29 2006-05-18 Microsoft Corporation Lossless adaptive golomb/rice encoding and decoding of integer data using backward-adaptive rules
US7158684B2 (en) 2002-04-25 2007-01-02 Texas Instruments Incoporated Entropy coding scheme for video coding
US20080013633A1 (en) 2006-07-12 2008-01-17 Yan Ye Video compression using adaptive variable length codes
US20080231483A1 (en) 2005-12-05 2008-09-25 Huawei Technologies Co., Ltd. Binarizing method and device thereof
US20080267513A1 (en) 2007-04-26 2008-10-30 Jagadeesh Sankaran Method of CABAC Significance MAP Decoding Suitable for Use on VLIW Data Processors
US20080310503A1 (en) * 2007-06-14 2008-12-18 Samsung Electronics Co., Ltd. Method and apparatus for entropy-coding/entropy-decoding video data
US20090175332A1 (en) 2008-01-08 2009-07-09 Qualcomm Incorporated Quantization based on rate-distortion modeling for cabac coders
US20090232204A1 (en) 2008-03-17 2009-09-17 Samsung Electronics Co., Ltd. Method and apparatus for encoding and decoding transform coefficients
US20110206289A1 (en) 2010-02-22 2011-08-25 Salih Dikbas Guaranteed-Rate Tiled Image Data Compression
US20120128067A1 (en) 2010-11-22 2012-05-24 Mediatek Singapore Pte. Ltd. Apparatus and Method of Constrained Partition Size for High Efficiency Video Coding
WO2012095488A2 (fr) 2011-01-14 2012-07-19 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Mode de codage et de décodage d'entropie
US20130016789A1 (en) 2011-07-15 2013-01-17 General Instrument Corporation Context modeling techniques for transform coefficient level coding
US20130114685A1 (en) 2011-11-07 2013-05-09 Sharp Laboratories Of America, Inc. Video decoder with constrained dynamic range
US20130114693A1 (en) * 2011-11-04 2013-05-09 Futurewei Technologies, Co. Binarization of Prediction Residuals for Lossless Video Coding
US20130188694A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130188727A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130188729A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130195370A1 (en) 2010-09-29 2013-08-01 Panasonic Corporation Image decoding method, image coding method, image decoding apparatus, image coding apparatus, program, and integrated circuit
US20130195182A1 (en) 2012-02-01 2013-08-01 General Instrument Corporation Simplification of significance map coding
US20130202029A1 (en) 2012-02-05 2013-08-08 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130202026A1 (en) 2012-02-04 2013-08-08 General Instrument Corporation Devices and methods for context reduction in last significant coefficient position coding
US20130322547A1 (en) 2011-11-08 2013-12-05 General Instrument Corporation Method of determining binary codewords for transform coefficients

Patent Citations (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6014095A (en) 1996-12-27 2000-01-11 Nec Corporation Variable length encoding system
US7158684B2 (en) 2002-04-25 2007-01-02 Texas Instruments Incoporated Entropy coding scheme for video coding
US20050123207A1 (en) 2003-12-04 2005-06-09 Detlev Marpe Video frame or picture encoding and decoding
US20060103556A1 (en) 2004-10-29 2006-05-18 Microsoft Corporation Lossless adaptive golomb/rice encoding and decoding of integer data using backward-adaptive rules
US20080231483A1 (en) 2005-12-05 2008-09-25 Huawei Technologies Co., Ltd. Binarizing method and device thereof
US20080013633A1 (en) 2006-07-12 2008-01-17 Yan Ye Video compression using adaptive variable length codes
US20080267513A1 (en) 2007-04-26 2008-10-30 Jagadeesh Sankaran Method of CABAC Significance MAP Decoding Suitable for Use on VLIW Data Processors
US20080310503A1 (en) * 2007-06-14 2008-12-18 Samsung Electronics Co., Ltd. Method and apparatus for entropy-coding/entropy-decoding video data
WO2008153270A1 (fr) 2007-06-14 2008-12-18 Samsung Electronics Co., Ltd. Procédé et appareil destinés à un codage entropique/décodage entropique de données vidéo
US20090175332A1 (en) 2008-01-08 2009-07-09 Qualcomm Incorporated Quantization based on rate-distortion modeling for cabac coders
US20090232204A1 (en) 2008-03-17 2009-09-17 Samsung Electronics Co., Ltd. Method and apparatus for encoding and decoding transform coefficients
US20110206289A1 (en) 2010-02-22 2011-08-25 Salih Dikbas Guaranteed-Rate Tiled Image Data Compression
US20130195370A1 (en) 2010-09-29 2013-08-01 Panasonic Corporation Image decoding method, image coding method, image decoding apparatus, image coding apparatus, program, and integrated circuit
US20120128067A1 (en) 2010-11-22 2012-05-24 Mediatek Singapore Pte. Ltd. Apparatus and Method of Constrained Partition Size for High Efficiency Video Coding
WO2012095488A2 (fr) 2011-01-14 2012-07-19 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Mode de codage et de décodage d'entropie
US20130016789A1 (en) 2011-07-15 2013-01-17 General Instrument Corporation Context modeling techniques for transform coefficient level coding
US20130114693A1 (en) * 2011-11-04 2013-05-09 Futurewei Technologies, Co. Binarization of Prediction Residuals for Lossless Video Coding
US20130114685A1 (en) 2011-11-07 2013-05-09 Sharp Laboratories Of America, Inc. Video decoder with constrained dynamic range
US20130322547A1 (en) 2011-11-08 2013-12-05 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130188694A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130188727A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130188729A1 (en) 2012-01-21 2013-07-25 General Instrument Corporation Method of determining binary codewords for transform coefficients
US20130195182A1 (en) 2012-02-01 2013-08-01 General Instrument Corporation Simplification of significance map coding
US20130202026A1 (en) 2012-02-04 2013-08-08 General Instrument Corporation Devices and methods for context reduction in last significant coefficient position coding
US20130202029A1 (en) 2012-02-05 2013-08-08 General Instrument Corporation Method of determining binary codewords for transform coefficients

Non-Patent Citations (38)

* Cited by examiner, † Cited by third party
Title
Aaron Kiely: "Selecting the Golomb Parameter in Rice Coding", IPN Progress Report,, vol. 42-159, Nov. 15, 2004, all pages.
Bankoski et al. "Technical Overview of VP8, an Open Source Video CODEC for the Web". Dated Jul. 11, 2011.
Bankoski et al. "VP8 Data Format and Decoding Guide" Independent Submission. RFC 6389, Dated Nov. 2011.
Bankoski et al. "VP8 Data Format and Decoding Guide; draft-bankoski-vp8-bitstream-02" Network Working Group. Internet-Draft, May 18, 2011, 288 pp.
Boss B et al. (WD4:Working Draft 4 of High-Efficiency Video Coding). *
Bross B et al.: "WD4: Working Draft 4 of High-Efficiency Video Coding", 6. JCT-VC Meeeting; 97. MPEG Meeting; Jul. 14, 2011-Jul. 22, 2011; Torino; (Joint Collaborative Team on Video Coding of ISO/IEC JTC1/SC29/WG11 and ITU-T SG.16(; URL:http://wftp3.itu.int/av-arch/jctvc-site/, No. JCTVC-F803, Sep. 8, 2011, all pages.
Heising et al., "CABAC and ABT" Joint Video Team (JVT) of ISO/IEC MEPG & ITU-T VCEG (ISO/IEC JTC1/SC29/W1 and ITU-T SG16 Q.6) 4th Meeting: Klagenfurt, Austria; Jul. 22-26, 2002; 14 pages.
Implementors' Guide; Series H: Audiovisual and Multimedia Systems; Coding of moving video: Implementors Guide for H.264: Advanced video coding for generic audiovisual services. H.264. International Telecommunication Union. Version 12. Dated Jul. 30, 2010.
ISR, "ISR Search Report and Written Opinion of the International Searching Authority" for International Application No. ISR/US2012/046960 dated Feb. 25, 2013, 19 pages.
ISR, "ISR Search Report and Written Opinion of the International Searching Authority" for International Application No. ISR/US2013/022306 dated Mar. 28, 2013, 14 pages.
ISR, "ISR Search Report and Written Opinion of the International Searching Authority" for International Application No. ISR/US2013/022312 dated Apr. 2013, 14 pages.
ISR, & Written Opinion of the International Searching Authority for International Application No. ISR/US2013/024654, May 7, 2013, 11 pages.
ISR, & Written Opinion of the International Searching Authority for International Application No. ISR/US2013/024786, May 21, 2013, 11 pages.
Joel Sole et al: "Transform Coefficienct Coding HEVC", IEEE Transactions on Cirucits and Systems For Video Technology, vol. 22, No. 12, Dec. 1, 2012, all pages, IEEE Service Center, Piscataway, NJ, US.
Kurcerin et al., "Improvements on CABAC" ITU-Telecommunications Standardization Sector; Study Group 16 Question 6; Video Coding Experts Group (VCEG) 14th Meeting: Santa Barbara, CA, USA; Sep. 24-27, 2001; 6 pages.
Malvar HS: "Adaptive run-length/Golomb-Rice encoding of quantized generalized Gaussian sources with unknown statistics", Proceedings, DCC 2006, Data Compression Conference, Mar. 28, 2006-Mar. 30, 2006, all pages, IEEE Compt. Society Los Alamitos, CA, USA.
Marpe et al., Context-Based Adaptive Binary Arithmetic Coding in the H.264/AVC Video Compression Standard, Detlev marpe, IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, No. 7, Jul. 2003, 17 pages.
Nguyen (Fraunhofer HHI) T: "CE11 Coding of transform coefficient levels with Golomb-Rice codes", Mar. 10, 2011, all pages.
Nguyen T et al.: "Reduced-complexity entropy coding of transform coefficient labels using a combination of VLC and PIPE", 4. JCT-VC Meeting; 95, MPEG Meeting; 201-1-2011-28-1-2011; Daegu; (Joint Collaborative Team on Video Coding of ISO/IEC JTC1/SC29/WG11and ITU-T SG.16); URL:http://wftp3.itu.int/av-arch/jctvc-site/, No. JCTVC-D336, Jan. 16, 2011, all pages.
Office Action mailed Dec. 18, 2014 in co-pending Japanese Application.
Overview; VP7 Data Format and Decoder. Version 1.5. On2 Technologies, Inc. Dated Mar. 28, 2005.
Patent Cooperation Treaty, International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/US2012/064229, Feb. 14, 2014, 1220 pages.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video. H.264. Advanced video coding for generic audiovisual services. International Telecommunication Union. Version 11. Dated Mar. 2009.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video. H.264. Advanced video coding for generic audiovisual services. International Telecommunication Union. Version 12. Dated Mar. 2010.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video. H.264. Advanced video coding for generic audiovisual services. Version 8. International Telecommunication Union. Dated Nov. 1, 2007.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video. H.264. Amendment 2: New profiles for professional applications. International Telecommunication Union. Dated Apr. 2007.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video; Advanced video coding for generic audiovisual services. H.264. Amendment 1: Support of additional colour spaces and removal of the High 4:4:4 Profile. International Telecommunication Union. Dated Jun. 2006.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video; Advanced video coding for generic audiovisual services. H.264. Version 1. International Telecommunication Union. Dated May 2003.
Series H: Audiovisual and Multimedia Systems; Infrastructure of audiovisual services-Coding of moving video; Advanced video coding for generic audiovisual services. H.264. Version 3. International Telecommunication Union. Dated Mar. 2005.
Sole et al., "Unified scans for the significance map and coefficient level coding in high coding efficiency," Joint Collaborative Team on Video Coding, JCTVCF-288 Geneva, Jul. 8, 2011.
Sze, "Reduction in contexts used for significant coeff-flag and coefficient level" Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T S6 WB3 and ISO/IEC JTC1/SC29/W1; 6th Meeting: Torino, IT; Jul. 14-22, 2011; 4 pages.
Tung Nguyen et al. (Reduced-complexity entropy coding of transform coefficient levels using truncated golomb-rice codes in video compression). *
Tung Nguyen et al.: "Reduced-complexity entropy coding of transform coeffient levels using truncated golomb-rice codes in video compression", Image Processing (ICIP), 2011 18th IEEE International Conference on, IEEE, Sep. 11, 2011, all pages.
VP6 Bitstream & Decoder Specification. Version 1.02. On2 Technologies, Inc. Dated Aug. 17, 2006.
VP6 Bitstream & Decoder Specification. Version 1.03. On2 Technologies, Inc. Dated Oct. 29, 2007.
VP8 Data Format and Decoding Guide. WebM Project. Google On2. Dated: Dec. 1, 2010.
Wiegand, T. "Joint Committee Draft" Draft ISO/IEC 14496-10: 2002 ( E ); Joint Video Team (JVT) of ISO/IEC MGPG and ITU-T-VCEG; 3rd Meeting; Fairfax, Virginia, USA; May 6-10, 2002; 142 pages.
Wien, Mathias "Variable Block-Size Transforms for Hybrid Video Coding" Dissertation Der Rheinisch-Westfaelischen Technischen Hochschule Aachen; Aachen, Germany; Feb. 3, 2004; 184 pages.

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12096024B2 (en) 2013-10-14 2024-09-17 Microsoft Technology Licensing, Llc Features of base color index map mode for video and image coding and decoding
US11758162B2 (en) 2014-09-30 2023-09-12 Microsoft Technology Licensing, Llc Rules for intra-picture prediction modes when wavefront parallel processing is enabled
US20200244962A1 (en) * 2015-06-09 2020-07-30 Microsoft Technology Licensing, Llc Robust encoding/decoding of escape-coded pixels in palette mode
US11539956B2 (en) * 2015-06-09 2022-12-27 Microsoft Technology Licensing, Llc Robust encoding/decoding of escape-coded pixels in palette mode
US20230091602A1 (en) * 2015-06-09 2023-03-23 Microsoft Technology Licensing, Llc Robust encoding/decoding of escape-coded pixels in palette mode
US20200267403A1 (en) * 2016-06-29 2020-08-20 Interdigital Vc Holdings, Inc. Method and apparatus for improved significance flag coding using simple local predictor
US11490104B2 (en) * 2016-06-29 2022-11-01 Interdigital Vc Holdings, Inc. Method and apparatus for improved significance flag coding using simple local predictor

Also Published As

Publication number Publication date
CN103931197A (zh) 2014-07-16
EP2777268A2 (fr) 2014-09-17
WO2013070970A2 (fr) 2013-05-16
KR20140098111A (ko) 2014-08-07
CN103931197B (zh) 2018-01-23
KR101660605B1 (ko) 2016-09-27
BR112014011150B1 (pt) 2022-08-09
US20130114698A1 (en) 2013-05-09
WO2013070970A3 (fr) 2014-04-10
BR112014011150A2 (pt) 2017-05-16

Similar Documents

Publication Publication Date Title
US10623742B2 (en) Method of determining binary codewords for transform coefficients
US9270988B2 (en) Method of determining binary codewords for transform coefficients
US9866850B2 (en) Method of determining binary codewords for transform coefficients
US9167245B2 (en) Method of determining binary codewords for transform coefficients
US9635358B2 (en) Method of determining binary codewords for transform coefficients
US20230037689A1 (en) Methods and apparatuses for coding transform blocks
US20130188729A1 (en) Method of determining binary codewords for transform coefficients
CN112352429B (zh) 对视频数据进行编解码的方法、设备和存储介质
US11451840B2 (en) Trellis coded quantization coefficient coding
WO2014120575A1 (fr) Codage entropique adaptatif au contenu de données de partition pour une vidéo de prochaine génération
US20240129512A1 (en) Encoding and decoding method, encoder, decoder, and storage medium
US10992937B2 (en) Coefficient coding with grouped bypass bins
EP2777279B1 (fr) Procédé de détermination de mots codés binaires pour des coefficients de transformée
JP2022548685A (ja) 画像データの符号化及び復号化
CN116918327A (zh) 视频编码中基于状态的依赖量化和残差编码

Legal Events

Date Code Title Description
AS Assignment

Owner name: GENERAL INSTRUMENT CORPORATION, PENNSYLVANIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LOU, JIAN;FANG, XUE;WANG, LIMIN;REEL/FRAME:029834/0342

Effective date: 20121114

AS Assignment

Owner name: MOTOROLA MOBILITY LLC, ILLINOIS

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:GENERAL INSTRUMENT HOLDINGS, INC.;REEL/FRAME:030866/0113

Effective date: 20130528

Owner name: GENERAL INSTRUMENT HOLDINGS, INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:GENERAL INSTRUMENT CORPORATION;REEL/FRAME:030764/0575

Effective date: 20130415

AS Assignment

Owner name: GOOGLE TECHNOLOGY HOLDINGS LLC, CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MOTOROLA MOBILITY LLC;REEL/FRAME:034274/0290

Effective date: 20141028

STCF Information on status: patent grant

Free format text: PATENTED CASE

FEPP Fee payment procedure

Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

LAPS Lapse for failure to pay maintenance fees

Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

PRDP Patent reinstated due to the acceptance of a late maintenance fee

Effective date: 20200407

FEPP Fee payment procedure

Free format text: SURCHARGE, PETITION TO ACCEPT PYMT AFTER EXP, UNINTENTIONAL (ORIGINAL EVENT CODE: M1558); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Free format text: PETITION RELATED TO MAINTENANCE FEES FILED (ORIGINAL EVENT CODE: PMFP); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Free format text: PETITION RELATED TO MAINTENANCE FEES GRANTED (ORIGINAL EVENT CODE: PMFG); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 4TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1551); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 4

STCF Information on status: patent grant

Free format text: PATENTED CASE

FP Lapsed due to failure to pay maintenance fee

Effective date: 20200223

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 8