US20080175502A1 - Method and system for providing arithmetic code normalization and byte construction - Google Patents
Method and system for providing arithmetic code normalization and byte construction Download PDFInfo
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- 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
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- This disclosure generally relates to the field of video data processing. More particularly, the disclosure relates to Context Adaptive Binary Arithmetic Coding (“CABAC”) for digital video encoders.
- CABAC Context Adaptive Binary Arithmetic Coding
- Video signals generally include data corresponding to one or more video frames.
- Each video frame is composed of an array of picture elements, which are called pixels.
- a typical color video frame having a standard resolution may be composed of over several hundreds of thousands of pixels, which are arranged in arrays of blocks.
- Each pixel is characterized by pixel data indicative of a hue (predominant color), saturation (color intensity), and luminance (color brightness).
- the hue and saturation characteristics may be referred to as the chrominance.
- the pixel data includes chrominance and luminance. Therefore, the pixel data may be represented by groups of four luminance pixel blocks and two chrominance pixel blocks. These groups are called macroblocks (“MBs”).
- MBs macroblocks
- the video frame As a video frame generally includes many pixels, the video frame also includes a large number of MBs. Thus, digital signals representing a sequence of video frame data, which usually include many video frames, have a large number of bits. However, the available storage space and bandwidth for transmitting these digital signals is limited. Therefore, compression processes are used to more efficiently transmit or store video data.
- VLC variable length coding
- Huffman Huffman coding
- blocks of symbols coding arithmetic coding
- CABAC Context Adaptive Binary Arithmetic Coding
- CABAC techniques are capable of losslessly compressing syntax elements in a video stream using the probabilities of syntax elements in a given context.
- the CABAC process will take in syntax elements representing all elements within a macroblock. Further, the CABAC process constructs a compress bit sequence by building out the following structure: the sequential set of fields for the macroblock based on the chosen macroblock configuration, the specific syntax element type and value for each of the fields within this field sequence, and the context address for each of the syntax elements.
- the CABAC process will then perform binarization of the syntax elements, update the context weights, arithmetically encode the binarizations of syntax elements (“bins”), and subsequently pack the bits into bytes through the syntax element processing component.
- the components of the CABAC process include: the CABAC weight initialization mode selection module, the macroblock syntax sequence generator, the binarization engine, the context address generator, the context weight update engine, the arithmetic coder, the bit packetizer, and the Network Abstraction Layer (“NAL”) header generator.
- the CABAC engine within a video encoder may accomplish two goals within the encoding process: (1) to carry out compressed data resource prediction for mode decision purposes; and (2) to losslessly compress the data for signal output delivery.
- the compressed data resource prediction task predicts the amount of bits required given a set of specific encoding modes for a given macroblock. Potential mode decision implementations may have up to eight modes to select from.
- the computational demand on the CABAC engine to support the mode decision task is significant.
- the weight update, arithmetic encoder and the bit packing components of the CABAC engine may require a significant amount of non-trivial computational and processing resources in a sequential processor implementation. Given that high performance encoding systems require multiple macro block rate distortion iterations of encoding per macro block, the CABAC process may impose an unreasonable resource demand on a processor-based solution. Prior implementations typically compromise on mode decision CABAC resource estimation accuracy by limiting the CABAC to bin level accuracy.
- a system capable of processing one binary symbol per clock cycle requires a matching back end-receiving engine capable of also processing the results on every cycle.
- the back end tasks consist of a value normalization task, which may generate up to eight bits of data, and a bit packing task, which groups the bits into bytes.
- the implementation solutions for the normalization and bit packing tasks are complex and computationally demanding.
- the first category includes routines that can generate at most one bit per cycle. This approach may utilize up to eight cycles to process one binary symbol as a single binary symbol may generate up to eight bits.
- the second category includes routines that achieve single cycle per binary symbol using a method that does not optimally handle all cases of the carry from the input data and the adder.
- a process extracts a plurality of subsets of bits from a first input. Each of the subsets of bits has a bit width equaling a number of leading zeros from a second input variable. Further, the process stores, in a memory, a consecutive sequence of the plurality of subsets. In addition, the process reads the consecutive sequence of the plurality of subsets from the memory if a third input release flag is established.
- a process stores a consecutive set of variable bit width data into a first in first out buffer.
- the variable bit width data has a width that is determined by a number of leading zeroes from an input variable. Further, the process reads the data from the first in first out buffer if the receiving data contains only ones.
- a process stores a consecutive set of data from a first input variable into a memory. Further, the process receives a subsequent data set from the first input variable. In addition, the process reads the consecutive set of data from the memory if the subsequent data set includes one or more binary bits having a value of zero.
- FIG. 1 illustrates a CABAC process
- FIG. 2 illustrates an arithmetic coder normalization process
- FIG. 3 illustrates an arithmetic coder normalization process that can process a new input data on every clock cycle.
- FIG. 4 illustrates a process for code normalization and byte construction.
- FIG. 5 illustrates another process for code normalization and byte construction.
- FIG. 6 illustrates yet another process for code normalization and byte construction.
- FIG. 7 illustrates a block diagram of a station or system that implements a code normalizer and byte construction engine.
- a method and system are disclosed, which provide an improved video digital data compression capable of providing a single cycle normalization for real-time digital video encoders, such as an MPEG-4 or an H-264 series encoder.
- the method and system may be utilized by the back end processor within the arithmetic encoder. As a result, normalization and payload to byte packing may be accomplished.
- FIG. 1 illustrates a CABAC process 100 .
- the CABAC process 100 selects a CABAC weight initialization mode.
- the CABAC process 100 generates an MB syntax sequence.
- the CABAC process 106 converts a syntax to binary.
- the term binarization may be utilized to denote the process block 106 .
- the CABAC process 100 performs a context address determination.
- the term ctxldx generation may be utilized to denote the process block 108 .
- the CABAC process 100 performs a context weight update.
- the CABAC process 100 performs an arithmetic encoding.
- the CABAC process 100 performs a bit packetizing.
- the CABAC process 100 performs a NAL header construction. An elementary stream results from the CABAC process 100 .
- FIG. 2 illustrates an arithmetic coder normalization process 200 .
- the arithmetic coder normalization process 200 can be utilized for the MPEG4 standard to process data at the bit level.
- the arithmetic coder normalization process 200 may utilize up to eight loop iterations to process a single binary input symbol from the front end arithmetic coder. Accordingly, an upper bound is placed on the computational demand.
- the arithmetic coder normalization process begins at a process block 202 . Further, at a process block 204 , the arithmetic coder normalization process 200 receives a codeLow input variable and a codeRange input variable.
- the codeLow input variable includes ten bits and the codeRange input variable includes nine bits.
- the arithmetic coder normalization process 200 increments an internal index. For example, the arithmetic coder normalization process 200 may increment an internal index “t” by one.
- the arithmetic coder normalization process 200 extracts the most significant bit from the codeLow input variable for a carry bit.
- the arithmetic coder normalization process 200 sets a variable to hold the number of leading zeros of the codeRange input variable. For example, the variable may be entitled shftCnt.
- the arithmetic coder normalization process 200 extracts a block of bits from the codeLow input variable. This is accomplished by discarding the most significant bits of the codeLow input variable and removing all the leading zeros to form a variable bit width block of bits.
- the variable bit width block of bits is then stored in a payload array at location t, which may be referred to by the variable payload[t].
- the arithmetic coder normalization process 200 determines if the contents of the variable payload[t], i.e., the bits, include only ones or both ones and zeroes. If the variable payload(t) includes both ones and zeroes, the arithmetic coder normalization process 200 proceeds to a process block 216 .
- the arithmetic coder normalization process begins with the first entry of the payload array. A carry is added to the first entry in the payload array. The payload is then outputted without the resulting carry. The arithmetic coder normalization process 200 then adds the carry from the addition of the first entry in the payload array to the second entry in the payload array.
- the payload is then outputted without the resulting carry.
- the arithmetic coder normalization process 200 then proceeds to a process block 220 to reset the payload array by setting the variable t to zero.
- the arithmetic coder normalization process 200 then ends at a process block 230 .
- the arithmetic coder normalization process 200 determines, at the decision block 212 , that the contents of the variable payload[t] include only ones, the arithmetic coder normalization process proceeds from the decision block 212 to the process block 222 .
- the carry bit is examined.
- the arithmetic coder normalization process 200 then proceeds to a decision block 224 to determine if the input carry bit equals one. If the arithmetic coder normalization process 200 determines that the input carry bit equals one, the arithmetic coder normalization process 200 proceeds to a process block 226 .
- the arithmetic coder normalization process 200 then proceeds to a process block 228 .
- the arithmetic coder normalization process 200 resets the index to negative one.
- the arithmetic coder normalization process 200 then ends at a process block 230 .
- the arithmetic coder normalization process 200 determines, at the decision block 224 , that the input carry bit does not equal one, the arithmetic coder normalization process 200 ends at the process block 230 .
- FIG. 3 illustrates a normalization and bit packing engine 300 capable of receiving one codeLow input and one code range input per cycle.
- This approach is based on binarization of syntax element (“bin”) level processing.
- a hardware solution is capable of providing a normalization and bit packing to bytes operation. This approach significantly reduces the hardware resources utilized by current systems. Specifically, this approach utilizes logic instead of memory lookup tables to resolve decision making tasks.
- the normalization and bit packing engine 300 receives two distinct variables: a codeLow variable 302 and a codeRange variable 304 , on every clock cycle.
- a leading zero detector 306 generates an output that is equal to the number of leading zero binary bits in the codeRange variable 304 . This output is registered in a latch shiftCnt 308 .
- a bus splitter 310 outputs a carry bit and a dchunk variable. The carry bit is extracted from the most significant bit of the codeLow variable 302 . Further, the dchunk variable, which includes the second through ninth lower bits of the codeLow variable 302 , is then shifted right by shiftCnt variable 308 through a shift latch 312 .
- the output dchunkRa of this shift latch 312 is then further shifted by bitPos 16 _ 1 variable through a bitPos 16 _ 1 shift latch 314 to align the data to fit into an output preparation register 316 .
- the output preparation register 316 is utilized to hold data until there are enough output bits to form a full byte. In another embodiment, a plurality of output preparation registers 316 may be utilized.
- a bit position calculator 318 generates a bitPos 16 _ 1 variable and a byte ready flag based on the input to the shiftCnt variable.
- the bitPos 16 _ 1 variable identifies where the dchunkR should reside within the output preparation register 316 .
- the byte ready flag identifies when the least significant byte 320 is ready for output.
- the bitPos 16 _ 1 shift latch 314 outputs dchunk 16 , which is then sent to a logical or gate 322 along with the output from the output preparation register 316 .
- the output from the logical or gate 322 is then sent to an adder 324 along with a shifted carry bit from a shift latch 326 to form both the output byte 328 and the new data for the output preparation register 316 .
- the shifted carry bit is generated by the shift latch 326 , which shifts the logically conditioned carry bit utilizing oneFlag_d, a delayed carry flag carry_d 6 , and a delayed carry flag carry_d 5 .
- the oneFlag_d is generated by first providing dchunk to an all ones detector 330 . If dchunk is all ones, the all ones detector 330 outputs oneFlag and provides oneFlag to a latch 332 . The latch 332 shifts oneFlag and outputs oneFlag_d.
- the oneFlag_d is provided along with a delayed carry flag carry_d 6 to a first gate 330 . Further, the output of the first gate 334 is provided along with a delayed carry flag carry_d 5 to a second gate 336 .
- the output of the adder 324 is split into a plurality of bytes through a bit splitter 338 .
- the bit splitter 338 splits the output of the adder 324 into three bytes. Further, in one embodiment, the bit splitter 338 is a twenty four bit splitter.
- the most significant byte is provided to an output byte register 340 , which may be denoted by the term outByte.
- the two least significant bytes are routed through a multiplexor 342 to feed the inputs of the output preparation register 316 . Based on the byteRdy flag, the multiplexor 342 selects one of the two lower output bytes from the adder 324 for the middle byte 344 of the output preparation register 316 .
- FIG. 4 illustrates a process 400 for code normalization and byte construction.
- the process 400 extracts a plurality of subsets of bits from a first input. Each of the subsets of bits has a bit width equaling a number of leading zeros from a second input variable.
- the process 400 stores, in a memory, a consecutive sequence of the plurality of subsets.
- the process 400 reads the consecutive sequence of the plurality of subsets from the memory if a third input release flag is established.
- FIG. 5 illustrates another process 500 for code normalization and byte construction.
- the process 500 stores a consecutive set of variable bit width data into a first in first out buffer.
- the variable bit width data has a width that is determined by a number of leading zeroes from an input variable.
- the process 500 reads the data from the first in first out buffer if the receiving data contains only ones.
- FIG. 6 illustrates yet another process 600 for code normalization and byte construction.
- the process 600 stores a consecutive set of data from a first input variable into a memory. Further, at a process block 604 , the process 600 receives a subsequent data set from the first input variable. In addition, at a process block 606 , the process 600 reads the consecutive set of data from the memory if the subsequent data set includes one or more binary bits having a value of zero.
- FIG. 7 illustrates a block diagram of a station or system 700 that implements a code normalizer and byte construction engine.
- the station or system 700 is implemented using a general purpose computer or any other hardware equivalents.
- the station or system 700 comprises a processor (“CPU”) 710 , a memory 720 , e.g., random access memory (“RAM”) and/or read only memory (ROM), a normalization and byte construction module 740 , and various input/output devices 730 , (e.g., storage devices, including but not limited to, a tape drive, a floppy drive, a hard disk drive or a compact disk drive, a receiver, a transmitter, a speaker, a display, an image capturing sensor, e.g., those used in a digital still camera or digital video camera, a clock, an output port, a user input device (such as a keyboard, a keypad, a mouse, and the like, or a microphone for capturing speech commands)).
- a user input device
- the code normalization and byte construction module 740 may be implemented as one or more physical devices that are coupled to the CPU 710 through a communication channel.
- the normalization and byte construction module 740 may be represented by one or more software applications (or even a combination of software and hardware, e.g., using application specific integrated circuits (ASIC)), where the software is loaded from a storage medium, (e.g., a magnetic or optical drive or diskette) and operated by the CPU in the memory 720 of the computer.
- ASIC application specific integrated circuits
- the normalization and byte construction module 740 (including associated data structures) of the present invention may be stored on a computer readable medium, e.g., RAM memory, magnetic or optical drive or diskette and the like.
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Abstract
Description
- 1. Field
- This disclosure generally relates to the field of video data processing. More particularly, the disclosure relates to Context Adaptive Binary Arithmetic Coding (“CABAC”) for digital video encoders.
- 2. General Background
- Video signals generally include data corresponding to one or more video frames. Each video frame is composed of an array of picture elements, which are called pixels. A typical color video frame having a standard resolution may be composed of over several hundreds of thousands of pixels, which are arranged in arrays of blocks. Each pixel is characterized by pixel data indicative of a hue (predominant color), saturation (color intensity), and luminance (color brightness). The hue and saturation characteristics may be referred to as the chrominance. Accordingly, the pixel data includes chrominance and luminance. Therefore, the pixel data may be represented by groups of four luminance pixel blocks and two chrominance pixel blocks. These groups are called macroblocks (“MBs”). As a video frame generally includes many pixels, the video frame also includes a large number of MBs. Thus, digital signals representing a sequence of video frame data, which usually include many video frames, have a large number of bits. However, the available storage space and bandwidth for transmitting these digital signals is limited. Therefore, compression processes are used to more efficiently transmit or store video data.
- Compression of digital video signals for transmission or for storage has become widely practiced in a variety of contexts. For example, multimedia environments for video conferencing, video games, Internet image transmissions, digital TV, and the like utilize compression. Coding and decoding are accomplished with coding processors. Examples of such coding processors include general computers, special hardware, multimedia boards, or other suitable processing devices. Further, the coding processors may utilize one of a variety of coding techniques, such as variable length coding (“VLC”), fixed coding, Huffman coding, blocks of symbols coding, and arithmetic coding. An example of arithmetic coding is Context Adaptive Binary Arithmetic Coding (“CABAC”).
- CABAC techniques are capable of losslessly compressing syntax elements in a video stream using the probabilities of syntax elements in a given context. The CABAC process will take in syntax elements representing all elements within a macroblock. Further, the CABAC process constructs a compress bit sequence by building out the following structure: the sequential set of fields for the macroblock based on the chosen macroblock configuration, the specific syntax element type and value for each of the fields within this field sequence, and the context address for each of the syntax elements. The CABAC process will then perform binarization of the syntax elements, update the context weights, arithmetically encode the binarizations of syntax elements (“bins”), and subsequently pack the bits into bytes through the syntax element processing component.
- The components of the CABAC process include: the CABAC weight initialization mode selection module, the macroblock syntax sequence generator, the binarization engine, the context address generator, the context weight update engine, the arithmetic coder, the bit packetizer, and the Network Abstraction Layer (“NAL”) header generator. The CABAC engine within a video encoder may accomplish two goals within the encoding process: (1) to carry out compressed data resource prediction for mode decision purposes; and (2) to losslessly compress the data for signal output delivery. The compressed data resource prediction task predicts the amount of bits required given a set of specific encoding modes for a given macroblock. Potential mode decision implementations may have up to eight modes to select from. The computational demand on the CABAC engine to support the mode decision task is significant.
- The weight update, arithmetic encoder and the bit packing components of the CABAC engine may require a significant amount of non-trivial computational and processing resources in a sequential processor implementation. Given that high performance encoding systems require multiple macro block rate distortion iterations of encoding per macro block, the CABAC process may impose an unreasonable resource demand on a processor-based solution. Prior implementations typically compromise on mode decision CABAC resource estimation accuracy by limiting the CABAC to bin level accuracy.
- A system capable of processing one binary symbol per clock cycle requires a matching back end-receiving engine capable of also processing the results on every cycle. The back end tasks consist of a value normalization task, which may generate up to eight bits of data, and a bit packing task, which groups the bits into bytes. The implementation solutions for the normalization and bit packing tasks are complex and computationally demanding.
- Current implementations of the normalization function for the CABAC arithmetic coder fall into two categories. The first category includes routines that can generate at most one bit per cycle. This approach may utilize up to eight cycles to process one binary symbol as a single binary symbol may generate up to eight bits. The second category includes routines that achieve single cycle per binary symbol using a method that does not optimally handle all cases of the carry from the input data and the adder.
- In one aspect of the disclosure, a process extracts a plurality of subsets of bits from a first input. Each of the subsets of bits has a bit width equaling a number of leading zeros from a second input variable. Further, the process stores, in a memory, a consecutive sequence of the plurality of subsets. In addition, the process reads the consecutive sequence of the plurality of subsets from the memory if a third input release flag is established.
- In another aspect, a process stores a consecutive set of variable bit width data into a first in first out buffer. The variable bit width data has a width that is determined by a number of leading zeroes from an input variable. Further, the process reads the data from the first in first out buffer if the receiving data contains only ones.
- In yet another aspect, a process stores a consecutive set of data from a first input variable into a memory. Further, the process receives a subsequent data set from the first input variable. In addition, the process reads the consecutive set of data from the memory if the subsequent data set includes one or more binary bits having a value of zero.
- The above-mentioned features of the present disclosure will become more apparent with reference to the following description taken in conjunction with the accompanying drawings wherein like reference numerals denote like elements and in which:
-
FIG. 1 illustrates a CABAC process. -
FIG. 2 illustrates an arithmetic coder normalization process. -
FIG. 3 illustrates an arithmetic coder normalization process that can process a new input data on every clock cycle. -
FIG. 4 illustrates a process for code normalization and byte construction. -
FIG. 5 illustrates another process for code normalization and byte construction. -
FIG. 6 illustrates yet another process for code normalization and byte construction. -
FIG. 7 illustrates a block diagram of a station or system that implements a code normalizer and byte construction engine. - A method and system are disclosed, which provide an improved video digital data compression capable of providing a single cycle normalization for real-time digital video encoders, such as an MPEG-4 or an H-264 series encoder. The method and system may be utilized by the back end processor within the arithmetic encoder. As a result, normalization and payload to byte packing may be accomplished.
-
FIG. 1 illustrates aCABAC process 100. At aprocess block 102, theCABAC process 100 selects a CABAC weight initialization mode. Further, at aprocess block 104, theCABAC process 100 generates an MB syntax sequence. In addition, at aprocess block 106, theCABAC process 106 converts a syntax to binary. The term binarization may be utilized to denote theprocess block 106. Further, at aprocess block 108, theCABAC process 100 performs a context address determination. The term ctxldx generation may be utilized to denote theprocess block 108. At aprocess block 110, theCABAC process 100 performs a context weight update. Further, at aprocess block 112, theCABAC process 100 performs an arithmetic encoding. In addition, at aprocess block 114, theCABAC process 100 performs a bit packetizing. Finally, at aprocess block 116, theCABAC process 100 performs a NAL header construction. An elementary stream results from theCABAC process 100. -
FIG. 2 illustrates an arithmeticcoder normalization process 200. In one embodiment, the arithmeticcoder normalization process 200 can be utilized for the MPEG4 standard to process data at the bit level. The arithmeticcoder normalization process 200 may utilize up to eight loop iterations to process a single binary input symbol from the front end arithmetic coder. Accordingly, an upper bound is placed on the computational demand. The arithmetic coder normalization process begins at aprocess block 202. Further, at aprocess block 204, the arithmeticcoder normalization process 200 receives a codeLow input variable and a codeRange input variable. In one embodiment, the codeLow input variable includes ten bits and the codeRange input variable includes nine bits. Further, at aprocess block 206, the arithmeticcoder normalization process 200 increments an internal index. For example, the arithmeticcoder normalization process 200 may increment an internal index “t” by one. In addition, at aprocess block 208, the arithmeticcoder normalization process 200 extracts the most significant bit from the codeLow input variable for a carry bit. At aprocess block 210, the arithmeticcoder normalization process 200 sets a variable to hold the number of leading zeros of the codeRange input variable. For example, the variable may be entitled shftCnt. Further, at anext process block 212, the arithmeticcoder normalization process 200 extracts a block of bits from the codeLow input variable. This is accomplished by discarding the most significant bits of the codeLow input variable and removing all the leading zeros to form a variable bit width block of bits. The variable bit width block of bits is then stored in a payload array at location t, which may be referred to by the variable payload[t]. - At a
decision block 214, the arithmeticcoder normalization process 200 determines if the contents of the variable payload[t], i.e., the bits, include only ones or both ones and zeroes. If the variable payload(t) includes both ones and zeroes, the arithmeticcoder normalization process 200 proceeds to aprocess block 216. At theprocess block 216, the arithmetic coder normalization process begins with the first entry of the payload array. A carry is added to the first entry in the payload array. The payload is then outputted without the resulting carry. The arithmeticcoder normalization process 200 then adds the carry from the addition of the first entry in the payload array to the second entry in the payload array. The payload is then outputted without the resulting carry. The arithmeticcoder normalization process 200 works through the entries payload array in a similar manner until the entry in payload(t-1) is processed. The iterations through these entries in the payload array may be denoted by the following code: for (i=0; i<t; i++) {payload[i]+=carry; Output(payload[i]}. Once the entry in payload[t-1] is processed, the arithmeticcoder normalization process 200 proceeds to aprocess block 218 where the most recent payload is moved to the base of the array, which may be denoted by payload[0]=payload[t]. The arithmeticcoder normalization process 200 then proceeds to aprocess block 220 to reset the payload array by setting the variable t to zero. The arithmeticcoder normalization process 200 then ends at aprocess block 230. - If the arithmetic
coder normalization process 200 determines, at thedecision block 212, that the contents of the variable payload[t] include only ones, the arithmetic coder normalization process proceeds from thedecision block 212 to theprocess block 222. At theprocess block 222, the carry bit is examined. The arithmeticcoder normalization process 200 then proceeds to adecision block 224 to determine if the input carry bit equals one. If the arithmeticcoder normalization process 200 determines that the input carry bit equals one, the arithmeticcoder normalization process 200 proceeds to aprocess block 226. At theprocess block 226, the arithmeticcoder normalization process 200 outputs all payload entries from index zero to index t sequentially beginning with the index zero. This approach can be denoted by the following code: for (i=0; i<=t; i++) {Output(payload[i])}. The arithmeticcoder normalization process 200 then proceeds to aprocess block 228. At theprocess block 228, the arithmeticcoder normalization process 200 resets the index to negative one. The arithmeticcoder normalization process 200 then ends at aprocess block 230. - If the arithmetic
coder normalization process 200 determines, at thedecision block 224, that the input carry bit does not equal one, the arithmeticcoder normalization process 200 ends at theprocess block 230. -
FIG. 3 illustrates a normalization andbit packing engine 300 capable of receiving one codeLow input and one code range input per cycle. This approach is based on binarization of syntax element (“bin”) level processing. In one embodiment, a hardware solution is capable of providing a normalization and bit packing to bytes operation. This approach significantly reduces the hardware resources utilized by current systems. Specifically, this approach utilizes logic instead of memory lookup tables to resolve decision making tasks. - The normalization and
bit packing engine 300 receives two distinct variables: a codeLow variable 302 and a codeRange variable 304, on every clock cycle. A leading zerodetector 306 generates an output that is equal to the number of leading zero binary bits in the codeRange variable 304. This output is registered in alatch shiftCnt 308. Abus splitter 310 outputs a carry bit and a dchunk variable. The carry bit is extracted from the most significant bit of the codeLow variable 302. Further, the dchunk variable, which includes the second through ninth lower bits of the codeLow variable 302, is then shifted right by shiftCnt variable 308 through ashift latch 312. The output dchunkRa of thisshift latch 312 is then further shifted by bitPos16_1 variable through abitPos16_1 shift latch 314 to align the data to fit into anoutput preparation register 316. Theoutput preparation register 316 is utilized to hold data until there are enough output bits to form a full byte. In another embodiment, a plurality of output preparation registers 316 may be utilized. - A
bit position calculator 318 generates a bitPos16_1 variable and a byte ready flag based on the input to the shiftCnt variable. The bitPos16_1 variable identifies where the dchunkR should reside within theoutput preparation register 316. The byte ready flag identifies when the leastsignificant byte 320 is ready for output. ThebitPos16_1 shift latch 314 outputs dchunk16, which is then sent to a logical orgate 322 along with the output from theoutput preparation register 316. The output from the logical orgate 322 is then sent to anadder 324 along with a shifted carry bit from ashift latch 326 to form both the output byte 328 and the new data for theoutput preparation register 316. The shifted carry bit is generated by theshift latch 326, which shifts the logically conditioned carry bit utilizing oneFlag_d, a delayed carry flag carry_d6, and a delayed carry flag carry_d5. - The oneFlag_d is generated by first providing dchunk to an all
ones detector 330. If dchunk is all ones, the allones detector 330 outputs oneFlag and provides oneFlag to alatch 332. Thelatch 332 shifts oneFlag and outputs oneFlag_d. - The oneFlag_d is provided along with a delayed carry flag carry_d6 to a
first gate 330. Further, the output of thefirst gate 334 is provided along with a delayed carry flag carry_d5 to asecond gate 336. - The output of the
adder 324 is split into a plurality of bytes through abit splitter 338. In one embodiment, thebit splitter 338 splits the output of theadder 324 into three bytes. Further, in one embodiment, thebit splitter 338 is a twenty four bit splitter. The most significant byte is provided to anoutput byte register 340, which may be denoted by the term outByte. The two least significant bytes are routed through amultiplexor 342 to feed the inputs of theoutput preparation register 316. Based on the byteRdy flag, themultiplexor 342 selects one of the two lower output bytes from theadder 324 for themiddle byte 344 of theoutput preparation register 316. -
FIG. 4 illustrates aprocess 400 for code normalization and byte construction. At aprocess block 402, theprocess 400 extracts a plurality of subsets of bits from a first input. Each of the subsets of bits has a bit width equaling a number of leading zeros from a second input variable. Further, at anext process block 404, theprocess 400 stores, in a memory, a consecutive sequence of the plurality of subsets. In addition, at aprocess block 406, theprocess 400 reads the consecutive sequence of the plurality of subsets from the memory if a third input release flag is established. -
FIG. 5 illustrates anotherprocess 500 for code normalization and byte construction. At aprocess block 502, theprocess 500 stores a consecutive set of variable bit width data into a first in first out buffer. The variable bit width data has a width that is determined by a number of leading zeroes from an input variable. Further, at aprocess block 504, theprocess 500 reads the data from the first in first out buffer if the receiving data contains only ones. -
FIG. 6 illustrates yet anotherprocess 600 for code normalization and byte construction. At aprocess block 602, theprocess 600 stores a consecutive set of data from a first input variable into a memory. Further, at aprocess block 604, theprocess 600 receives a subsequent data set from the first input variable. In addition, at aprocess block 606, theprocess 600 reads the consecutive set of data from the memory if the subsequent data set includes one or more binary bits having a value of zero. -
FIG. 7 illustrates a block diagram of a station orsystem 700 that implements a code normalizer and byte construction engine. In one embodiment, the station orsystem 700 is implemented using a general purpose computer or any other hardware equivalents. Thus, the station orsystem 700 comprises a processor (“CPU”) 710, amemory 720, e.g., random access memory (“RAM”) and/or read only memory (ROM), a normalization andbyte construction module 740, and various input/output devices 730, (e.g., storage devices, including but not limited to, a tape drive, a floppy drive, a hard disk drive or a compact disk drive, a receiver, a transmitter, a speaker, a display, an image capturing sensor, e.g., those used in a digital still camera or digital video camera, a clock, an output port, a user input device (such as a keyboard, a keypad, a mouse, and the like, or a microphone for capturing speech commands)). - It should be understood that the code normalization and
byte construction module 740 may be implemented as one or more physical devices that are coupled to theCPU 710 through a communication channel. Alternatively, the normalization andbyte construction module 740 may be represented by one or more software applications (or even a combination of software and hardware, e.g., using application specific integrated circuits (ASIC)), where the software is loaded from a storage medium, (e.g., a magnetic or optical drive or diskette) and operated by the CPU in thememory 720 of the computer. As such, the normalization and byte construction module 740 (including associated data structures) of the present invention may be stored on a computer readable medium, e.g., RAM memory, magnetic or optical drive or diskette and the like. - It is understood that the normalization and byte construction engine described herein may also be applied in other type of encoders. Those skilled in the art will appreciate that the various adaptations and modifications of the embodiments of this method and apparatus may be configured without departing from the scope and spirit of the present method and system. Therefore, it is to be understood that, within the scope of the appended claims, the present method and apparatus may be practiced other than as specifically described herein.
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