Abstract:
A system is provided for creating level parameter updating codewords for transform coefficients used for relating transform units (TUs) that divide up coding units (CUs) in a High Efficiency Video Coding (HEVC) system. The system provides binarization of the codewords and removes unnecessary operations to reduce system complexity and increase compression performance. The system generates transform coefficients that relate the TUs and begins by providing a parameter variable (cRiceParam) set to an initial value of zero. The parameter variable is then converted into a binary codeword based on the current value of the parameter variable and the value of a symbol and then updated with a new current value after each symbol has been converted. Updating can be provided with reference to table values or the values can be provided from combination logic.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This Application claims priority under 35 U.S.C. §119(e) from: earlier filed U.S. Provisional Application Ser. No. 61/556,826, filed Nov. 8, 2011; earlier filed U.S. Provisional Application Ser. No. 61/563,774, filed Nov. 26, 2011; and earlier filed U.S. Provisional Application Ser. No. 61/564,248, filed Nov. 28, 2011, the entirety of which are incorporated herein by reference. 
    
    
     BACKGROUND 
     1. Technical Field 
     The present disclosure relates to the field of video compression, particularly video compression using High Efficiency Video Coding (HEVC) that employ block processing. 
     2. Related Art 
       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. In some embodiments, 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. In response to the encoding control signal  124  from the controller  111 , 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. 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 . 
     The encoded video signal  122 , including the generated video compression data, 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 . 
     In some embodiments, 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. 
     In some embodiments, when the frame number signal  163  indicates the receiver buffer  150  is at a predetermined capacity, the controller  153  can output a decoding start signal  164  to the decoding unit  151 . When the frame number signal  163  indicates the receiver buffer  150  is at less than a predetermined capacity, 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. By way of a non-limiting example, 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. 
     In response to the decoding start signal  164 , 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 . 
     In various embodiments, 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. In HEVC, 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. As shown in  FIG. 3 , each LCU  200  can be partitioned by splitting the LCU  200  into four Coding Units (CUs)  202 . 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. 
     With higher and higher video data density, what is needed are further improved ways to code the CUs so that large input images and/or macroblocks can be rapidly, efficiently and accurately encoded and decoded. 
     SUMMARY 
     The present invention provides an improved system for HEVC. In embodiments for the system, 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. 
     In one embodiment, a method is provided that 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. 
     In another embodiment, 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. 
     In another embodiment, 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. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Further details of the present invention are explained with the help of the attached drawings in which: 
         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. 
     
    
    
     DETAILED DESCRIPTION  
     In HEVC, an input image, such as a video frame, is broken up into CUs that are then identified in code. The CUs are then further broken into sub-units that are coded as will be described subsequently. 
     Initially for the coding 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 . At each node of the quadtree representation, 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. By way of a non-limiting example, 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. By way of a non-limiting example, the CU split flag quadtree representation shown in  FIG. 4  can be coded as the binary data representation “10100.” 
     At each leaf of the quadtree, 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. In intra mode 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. In some embodiments, brightness information (Luma) and color information (Chroma) for the PU  204  can be predicted separately. In some embodiments, 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. In alternate embodiments, 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. In some embodiments, 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. In 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. In some embodiments, the motion vectors can be coded as syntax elements “MV,” and the reference pictures can be coded as syntax elements “refIdx.” In some embodiments, 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. At  606  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. At  608  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 . In some embodiments, the block transform can be square. In alternate embodiments, the block transform can be non-square. 
     As shown in  FIG. 7 , in HEVC, 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. By way of a non-limiting example, the quadtree representation shown in  FIG. 8  depicts the arrangement of TUs  210  within the CU  202  shown in  FIG. 7 . 
     Referring back to  FIG. 6 , at  610  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. After the transform coefficients  212  have been quantized, at  612  the quantized transform coefficients  212  can be entropy coded, as discussed below, to obtain the final compression bits  214 . 
     At  614  the quantized transform coefficients  212  can be dequantized into dequantized transform coefficients  216  E′. At  616  the dequantized transform coefficients  216  E′ can then be inverse transformed to reconstruct the residual PU  218 , e′. At  618  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″. At  620  a deblocking filter can be used on reconstructed PUs  220 , x″, to reduce blocking artifacts. At  620  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. 
     If 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). The coding process for CABAC is shown in  FIG. 9 . At  902 , the position of the last significant transform coefficient of the transform units  210  can be coded. Referring back to  FIG. 6 , 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. In some embodiments, 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. In some embodiments, these coordinates can be coded as the syntax elements “last_significant_coeff_y” and “last_significant_coeff_x.” By way of a non-limiting example,  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 . 
     At block  904  in  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. In some embodiments, the groups can be sub-blocks. Sub-blocks can be square blocks of 16 quantized transform coefficients  212 . In other embodiments, 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. By way of a non-limiting example, the last significant transform coefficient  212   b  can be the 14th transform coefficient  212  in the subset, followed by two insignificant transform coefficients. 
     In some situations and/or embodiments, there can be one or more groups of 16 quantized transform coefficients  212  that do not contain a significant transform coefficient along the reverse scan order prior to the group containing the last significant transform coefficient  212   b . In these situations and/or embodiments, 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 . By way of a non-limiting example, in  FIG. 11 , 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. In some embodiments, 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 . 
     Referring back to  FIG. 9  in the last block  906 , 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. During coding 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. By way of a non-limiting example, in some embodiments 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. First, 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. 
     At  1206  in  FIG. 12 , if the coefficient level  222  is greater than two, the coefficient level  222  can be subtracted by a threshold value  224  of three to obtain a symbol. By way of a non-limiting example, in some embodiments, 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.” For quantized transform coefficients  212  with a coefficient level  222  of two or more, “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 threshold value  224  of three can be subtracted from the coefficient level  222  to get the quantized transform coefficient&#39;s symbol  226 , coded as “coeff_abs_level_minus3.” In alternate embodiments, the coefficient level  222  can be coded in a different number of parts, and/or the threshold value  224  can be an integer other than three. 
     For the quantized transform coefficients  212  that occur less frequently and have coefficient levels  222  of three or more as determined in the blocks of  FIG. 12 , as determined in the blocks of  FIG. 12 , the quantized transform coefficient&#39;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 . In some embodiments, the current scanning position can be denoted by “n.” 
     Referring to  FIG. 15 , 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. In some embodiments, the parameter variable  230  can be any integer between 0 and N. By way of a non-limiting example, in some embodiments N can be 3, such that the parameter variable  230  can be 0, 1, 2, or 3. In some embodiments, the parameter variable  230  can be denoted as “cRiceParam” as illustrated in  FIG. 15  as well as  FIG. 14 . 
     Referring still to  FIG. 14 , each parameter variable  230  can have an associated maximum symbol value  232  that denotes the truncation point for the Truncated Rice code. In some embodiments, 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. 15  is less than or equal to the maximum symbol value  232  for the parameter variable  230 , the symbol  226  can be converted into a binary codeword  228  using only Truncated Rice code. If the symbol  226  is greater than the maximum symbol value  232  for the parameter variable  230 , the binary codeword  228  can be generated using a combination of the Truncated Rice code and Exp-Golomb code, with the Truncated Rice codeword for the maximum symbol value  232  being concatenated with the 0th order Exp-Golomb code for the symbol  226  minus the maximum symbol value  232  minus one. By way of a non-limiting example,  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. 
     In some situations and/or embodiments, 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 . By way of a non-limiting example, as shown by the table depicted in  FIG. 15 , 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. 
     In other situations and/or embodiments, 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 . By way of a non-limiting example, as shown in the table depicted in  FIG. 14 , 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 . At  1602 , for each TU  210 , the parameter variable  230  can be initially set to a value of zero. At  1604  the coding system  110  can move to the next symbol  226 . In some situations and/or embodiments, the next symbol  226  can be the first symbol  226  in the first subset  1102  as illustrated in  FIG. 11 . At  1606 , the symbol  226  can be coded with Truncated Rice and/or Exp-Golomb code using the current value of the parameter variable  230 . At  1608 , 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. In some situations and/or embodiments, 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. 
     After the parameter variable  230  has been updated at  1608 , 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 . In some embodiments, when symbols  226  in a subsequent subset  1102  are coded, 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 . In alternate embodiments, the parameter variable  230  can be set to zero at the first symbol  226  of each subset  1102 . 
     Generally referring to  FIG. 15 , 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. 
     In one embodiment illustrated with the table of  FIG. 17 , 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. 
     Note that in conventional implementations, cRiceParam  230  is reset once per subset with initial “0” values. For a TU with more than one subset of 16 consecutive symbol coefficients  226 , the cRiceParam calculation for coeff_abs_level_minus3 can be reset to 0 for each subset, which favors smaller symbol value coding. Generally, inside each TU, starting from the last non-zero quantized transform coefficient, 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. 
     In  FIG. 13 , 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. Following the reverse scanning pattern, 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 . In the example, 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 . In conventional implementations, 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. 
     Tables 4 and 5 as illustrated in respective  FIGS. 18 and 19  depict alternate embodiments on an update table. For these and other embodiments, 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. 
     By not resetting the cRiceParam to 0 at each subset, the operations of resetting for each subset are saved and once the cRiceParam reaches 3, the symbols will always be binarized with the same set truncated rice codes (cRiceParam equals 3), which can reduce hardware complexity. 
     Note that 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. 
     In some embodiments, updating the parameter variable  230  at  1608 , referring back to  FIG. 16 , 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 . In some embodiments, 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. 
     In some embodiments, 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 . 
     Since updating tables can need extra memory to store and fetch the data and the memory can require a lot of processor cycles, it can be preferable to use combination logics to perform the comparison in place of an updating table as the logic can use very few processor cycles. An example of the combination logic that determines the cRiceParam for updating in the place of Table 3 is shown in  FIG. 20 . An example of combination logic for representing Table 4 is shown in  FIG. 21 . An example of combination logic for representing Table 5 is shown in  FIG. 22 . 
     In some embodiments, 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. In these embodiments, 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 . 
     In further embodiments, 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 . For 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. 
     Further in this low complexity level parameter updating tables, the following further applies: (1) 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 . The combination logic representation for Table 6 is depicted in  FIG. 24 . The values of A, B, and C can be set to any desired values. In this exemplary embodiment, 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. 
     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. 
     The execution of the sequences of instructions required to practice the embodiments may be performed by a computer system  3300  as shown in  FIG. 20 . In an embodiment, execution of the sequences of instructions is performed by a single computer system  3300 . According to other embodiments, two or more computer systems  3300  coupled by a communication link  3315  may perform the sequence of instructions in coordination with one another. Although 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. 
     A computer system  3300  according to an embodiment will now be described with reference to  FIG. 20 , which is a block diagram of the functional components of a computer system  3300 . As used herein, 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 . For example, the communication link  3315  may be a LAN, an integrated services digital network (ISDN) card, a modem, or the Internet. 
     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. 
     In an embodiment, 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. 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 . 
     According to one embodiment, 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. In alternative embodiments, 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. 
     Although the present invention has been described above with particularity, this was merely to teach one of ordinary skill in the art how to make and use the invention. Many additional modifications will fall within the scope of the invention, as that scope is defined by the following claims.