Practical Implementations of Arithmetic Coding

Howard, Paul G.; Vitter, Jeffrey Scott

doi:10.1007/978-1-4615-3596-6_4

Cited by 121 publications

(77 citation statements)

References 45 publications

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“…In the following, we consider three variations of PPM: PPMA, PPMC, and PPMD [3,10]. The variations differ how the escape probability and the symbol probability Ô for symbol are computed.…”

Section: Application Of the Ppm Approachmentioning

confidence: 99%

“…Variation PPMD is defined in Table 1 in an alternative way which is equivalent to the original definition [10]. Next we will consider how the PPM technique can applied to compression of parse trees.…”

Section: Application Of the Ppm Approachmentioning

confidence: 99%

“…For low-level encoding, arithmetic coding [10,21] gives the best compression. The idea of arithmetic coding is as follows.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On compression of parse trees

Tarhio¹

2001

Proceedings Eighth Symposium on String Processing and Information Retrieval

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“…In the following, we consider three variations of PPM: PPMA, PPMC, and PPMD [3,10]. The variations differ how the escape probability and the symbol probability Ô for symbol are computed.…”

Section: Application Of the Ppm Approachmentioning

confidence: 99%

Section: Application Of the Ppm Approachmentioning

confidence: 99%

See 1 more Smart Citation

On compression of parse trees

Tarhio¹

2001

Proceedings Eighth Symposium on String Processing and Information Retrieval

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“…It enables much functionality potential accessible on a single terminal and higher levels of interaction with content. MPEG-4 achieves these goals by providing standardized ways to support: coding, composition, multiplexing and interaction [3,4]. The key feature of MPEG-4 is decompose a video frames in different layers of video object plane (VOP).…”

Section: Introduction To Mpeg-4 Videomentioning

confidence: 99%

Performance evaluation of entropy coding for MPEG-4 video codec

Nigam¹,

Mishra²,

Diwakar³

2014

International Advanced Research Journal in Science, Engineering

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This Paper deals with the Evaluation, Analysis and Algorithm of Context Adaptive Binary Arithmetic coding (CABAC) MPEG-4 Video Codec.MPEG-4 is an ISO/IEC video coding standard which supports highly interactive multimedia applications as well as traditional applications. It includes many advanced functionalities such as interactivities, scalabilities and error resilience. The growing popularity of MPEG-4 in the field of animation and interactive movies was the main motivation to include it in this work. This paper investigates the effect of CABAC Entropy coding scheme that is a crucial parameter for the performance of MPEG-4 video coder. In this paper Algorithm for Context Adaptive Binary Arithmetic coding (CABAC) is proposed for MPEG-4 Video Codec. The compression efficiency of CABAC is 8-12% better as compared to CAVLC and it can be up to 30% better when compared to other entropy compression methods.

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“…In arithmetic coding, cumulative probabilities of symbols are used to compute subintervals in the range [0, 1). In implementations [1,6,8,[12][13][14][15] with integer arithmetic, cumulative frequencies are used instead of cumulative probabilities. Algorithms for adaptive arithmetic coding need building statistical data model of cumulative frequencies on fly.…”

Section: Introductionmentioning

confidence: 99%

Implementing a Novel Data Structure for Maintaining Cumulative Frequency of Symbols

Doshi¹,

Gandhi²

2012

IJCA

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A new data structure, namely "cumulative frequency matrix (CFM)", is proposed here for maintaining cumulative frequencies. For an order-0 model having 256 symbols, CFM is a 2-D array of 16 rows and 16 columns. Two nibbles, say L for left and R for right, of a byte symbol represents row and column dimensions respectively. Matrix element (L, R) represents cumulative frequency of symbol with right nibble as R among symbols with left nibble as L. Within row, it stores cumulative frequency of symbols with right nibble varying from 0 to 15. Adaptive arithmetic coding is a lossless data compression method. It needs to update cumulative frequencies at runtime. Various algorithms for maintaining cumulative frequencies, computing cumulative frequency interval etc. are discussed here. Practical implementation shows that proposed data structure is simpler as well as efficient as compared to other data structures in use.

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Practical Implementations of Arithmetic Coding

Cited by 121 publications

References 45 publications

On compression of parse trees

On compression of parse trees

Performance evaluation of entropy coding for MPEG-4 video codec

Implementing a Novel Data Structure for Maintaining Cumulative Frequency of Symbols

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