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CABAC
Context-adaptive binary arithmetic coding (CABAC) is a form of entropy encoding used in the H.264/MPEG-4 AVC and High Efficiency Video Coding (HEVC) standards. It is a lossless compression technique, although the video coding standards in which it is used are typically for lossy compression applications. CABAC is notable for providing much better compression than most other entropy encoding algorithms used in video encoding, and it is one of the key elements that provides the H.264/AVC encoding scheme with better compression capability than its predecessors. In H.264/MPEG-4 AVC, CABAC is only supported in the Main and higher profiles (but not the extended profile) of the standard, as it requires a larger amount of processing to decode than the simpler scheme known as context-adaptive variable-length coding (CAVLC) that is used in the standard's Baseline profile. CABAC is also difficult to parallelize and vectorize, so other forms of parallelism (such as spatial region parallelis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CABAC Encoder Workflow Diagram
Context-adaptive binary arithmetic coding (CABAC) is a form of entropy encoding used in the H.264/MPEG-4 AVC and High Efficiency Video Coding (HEVC) standards. It is a lossless compression technique, although the video coding standards in which it is used are typically for lossy compression applications. CABAC is notable for providing much better compression than most other entropy encoding algorithms used in video encoding, and it is one of the key elements that provides the H.264/AVC encoding scheme with better compression capability than its predecessors. In H.264/MPEG-4 AVC, CABAC is only supported in the Main and higher profiles (but not the extended profile) of the standard, as it requires a larger amount of processing to decode than the simpler scheme known as context-adaptive variable-length coding (CAVLC) that is used in the standard's Baseline profile. CABAC is also difficult to parallelize and vectorize, so other forms of parallelism (such as spatial region parallelis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
High Efficiency Video Coding
High Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H Part 2, is a video coding format, video compression standard designed as part of the MPEG-H project as a successor to the widely used Advanced Video Coding (AVC, H.264, or MPEG-4 Part 10). In comparison to AVC, HEVC offers from 25% to 50% better data compression at the same level of video quality, or substantially improved video quality at the same bit rate. It supports resolutions up to 8192×4320, including Ultra-high-definition television, 8K UHD, and unlike the primarily 8-bit AVC, HEVC's higher fidelity Main 10 profile has been incorporated into nearly all supporting hardware. While AVC uses the integer discrete cosine transform (DCT) with 4×4 and 8×8 block sizes, HEVC uses integer DCT and Discrete sine transform, DST transforms with varied block sizes between 4×4 and 32×32. The High Efficiency Image File Format, High Efficiency Image Format (HEIF) is based on HEVC. , HEVC is used by 43% of video develope ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CAVLC
Context-adaptive variable-length coding (CAVLC) is a form of entropy coding used in H.264/MPEG-4 AVC video encoding. It is an inherently lossless compression technique, like almost all entropy-coders. In H.264/MPEG-4 AVC, it is used to encode residual, zig-zag order, blocks of transform coefficients. It is an alternative to context-based adaptive binary arithmetic coding (CABAC). CAVLC requires considerably less processing to decode than CABAC, although it does not compress the data quite as effectively. CAVLC is supported in all H.264 profiles, unlike CABAC which is not supported in Baseline and Extended profiles. CAVLC is used to encode residual, zig-zag ordered 4×4 (and 2×2) blocks of transform coefficients. CAVLC is designed to take advantage of several characteristics of quantized 4×4 blocks: * After prediction, transformation and quantization, blocks are typically sparse (containing mostly zeros). * The highest non-zero coefficients after zig-zag scan are often sequenc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Context-adaptive Variable-length Coding
Context-adaptive variable-length coding (CAVLC) is a form of entropy coding used in H.264/MPEG-4 AVC video encoding. It is an inherently lossless compression technique, like almost all entropy-coders. In H.264/MPEG-4 AVC, it is used to encode residual, zig-zag order, blocks of transform coefficients. It is an alternative to context-based adaptive binary arithmetic coding (CABAC). CAVLC requires considerably less processing to decode than CABAC, although it does not compress the data quite as effectively. CAVLC is supported in all H.264 profiles, unlike CABAC which is not supported in Baseline and Extended profiles. CAVLC is used to encode residual, zig-zag ordered 4×4 (and 2×2) blocks of transform coefficients. CAVLC is designed to take advantage of several characteristics of quantized 4×4 blocks: * After prediction, transformation and quantization, blocks are typically sparse (containing mostly zeros). * The highest non-zero coefficients after zig-zag scan are often sequenc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Context-adaptive Variable-length Coding
Context-adaptive variable-length coding (CAVLC) is a form of entropy coding used in H.264/MPEG-4 AVC video encoding. It is an inherently lossless compression technique, like almost all entropy-coders. In H.264/MPEG-4 AVC, it is used to encode residual, zig-zag order, blocks of transform coefficients. It is an alternative to context-based adaptive binary arithmetic coding (CABAC). CAVLC requires considerably less processing to decode than CABAC, although it does not compress the data quite as effectively. CAVLC is supported in all H.264 profiles, unlike CABAC which is not supported in Baseline and Extended profiles. CAVLC is used to encode residual, zig-zag ordered 4×4 (and 2×2) blocks of transform coefficients. CAVLC is designed to take advantage of several characteristics of quantized 4×4 blocks: * After prediction, transformation and quantization, blocks are typically sparse (containing mostly zeros). * The highest non-zero coefficients after zig-zag scan are often sequenc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Encoding
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have expected code length greater or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \mathbb E_(d(x))\geq \mathbb E_ \log_b(P(x))/math>, where l is the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code may be useful. These static codes ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arithmetic Coding
Arithmetic coding (AC) is a form of entropy encoding used in lossless data compression. Normally, a string of characters is represented using a fixed number of bits per character, as in the ASCII code. When a string is converted to arithmetic encoding, frequently used characters will be stored with fewer bits and not-so-frequently occurring characters will be stored with more bits, resulting in fewer bits used in total. Arithmetic coding differs from other forms of entropy encoding, such as Huffman coding, in that rather than separating the input into component symbols and replacing each with a code, arithmetic coding encodes the entire message into a single number, an arbitrary-precision fraction ''q'', where . It represents the current information as a range, defined by two numbers. A recent family of entropy coders called asymmetric numeral systems allows for faster implementations thanks to directly operating on a single natural number representing the current information ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arithmetic Coding
Arithmetic coding (AC) is a form of entropy encoding used in lossless data compression. Normally, a string of characters is represented using a fixed number of bits per character, as in the ASCII code. When a string is converted to arithmetic encoding, frequently used characters will be stored with fewer bits and not-so-frequently occurring characters will be stored with more bits, resulting in fewer bits used in total. Arithmetic coding differs from other forms of entropy encoding, such as Huffman coding, in that rather than separating the input into component symbols and replacing each with a code, arithmetic coding encodes the entire message into a single number, an arbitrary-precision fraction ''q'', where . It represents the current information as a range, defined by two numbers. A recent family of entropy coders called asymmetric numeral systems allows for faster implementations thanks to directly operating on a single natural number representing the current information ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Texas Instruments
Texas Instruments Incorporated (TI) is an American technology company headquartered in Dallas, Texas, that designs and manufactures semiconductors and various integrated circuits, which it sells to electronics designers and manufacturers globally. It is one of the top 10 semiconductor companies worldwide based on sales volume. The company's focus is on developing analog chips and embedded processors, which account for more than 80% of its revenue. TI also produces TI digital light processing technology and education technology products including calculators, microcontrollers, and multi-core processors. The company holds 45,000 patents worldwide as of 2016. Texas Instruments emerged in 1951 after a reorganization of Geophysical Service Incorporated, a company founded in 1930 that manufactured equipment for use in the seismic industry, as well as defense electronics. TI produced the world's first commercial silicon transistor in 1954, and the same year designed and manufac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Southern California
, mottoeng = "Let whoever earns the palm bear it" , religious_affiliation = Nonsectarian—historically Methodist , established = , accreditation = WSCUC , type = Private research university , academic_affiliations = , endowment = $8.12 billion (2021)As of June 30, 2021. , budget = $6.2 billion (2020–21) , president = Carol Folt , students = 49,318 (2021) , undergrad = 20,790 (2021) , postgrad = 28,528 (2021) , faculty = 4,706 (2021) , administrative_staff = 16,614 (2021) , city = , state = , country = United States , campus = Large City University Park campus, Heal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
