Length-limited variable-to-variable length codes for high-performance entropy coding

Senecal, Joshua G.; Duchaineau, Mark A.; Joy, Ken

doi:10.1109/dcc.2004.1281484

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Quantized coefficients fall into a range of uncertainty. For example, if the coefficient 42 (00101010) is quantized to 5 bits of precision, it falls into the range [40,47].…”

Section: Quantization and Psnrmentioning

confidence: 99%

Length-Limited Data Transformation and Compression

Joy

Senecal

2005

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Scientific computation is used for the simulation of increasingly complex phenomena, and generates data sets of ever increasing size, often on the order of terabytes. All of this data creates difficulties. Several problems that have been identified are (1) the inability to effectively handle the massive amounts of data created, (2) the inability to get the data off the computer and into storage fast enough, and (3) the inability of a remote user to easily obtain a rendered image of the data resulting from a simulation run. This dissertation presents several techniques that were developed to address these issues. The first is a prototype bin coder based on variable-tovariable length codes. The codes utilized are created through a process of parse tree leaf merging, rather than the common practice of leaf extension. This coder

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“…Quantized coefficients fall into a range of uncertainty. For example, if the coefficient 42 (00101010) is quantized to 5 bits of precision, it falls into the range [40,47].…”

Section: Quantization and Psnrmentioning

confidence: 99%

Length-Limited Data Transformation and Compression

Joy

Senecal

2005

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“…Twenty-six years ago, in one of the earliest attempts at V2V code construction, Fabris already hinted at "no algorithmic solution better than exhaustive search" [21]. Later, non-optimal construction methods were provided in [22] and in [23], where low-redundancy (and even vanishing-redundancy) codes are achieved at the expense of increased code tables. Fortunately, V2V codes with precomputed code tables of manageable size can be used in practice, as illustrated for example by their use in [24], where they are employed as a higher-efficiency replacement for Golomb codes [25].…”

Section: Introductionmentioning

confidence: 99%

Lower Bounds on the Redundancy of Huffman Codes With Known and Unknown Probabilities

Blanes¹,

Hernández-Cabronero²,

Serra-Sagristà³

et al. 2019

IEEE Access

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In this paper we provide a method to obtain tight lower bounds on the minimum redundancy achievable by a Huffman code when the probability distribution underlying an alphabet is only partially known. In particular, we address the case where the occurrence probabilities are unknown for some of the symbols in an alphabet. Bounds can be obtained for alphabets of a given size, for alphabets of up to a given size, and for alphabets of arbitrary size. The method operates on a Computer Algebra System, yielding closed-form numbers for all results. Finally, we show the potential of the proposed method to shed some light on the structure of the minimum redundancy achievable by the Huffman code.

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“…The scheme incorporates variable run-length coding and Golomb codes [17] which provide a unique binary representation for run-length integer symbol with different lengths. It also offers a fast decoding algorithm as reported in [18].…”

Section: Introductionmentioning

confidence: 99%

A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression

Salleh

Soraghan

2007

EURASIP J. Adv. Signal Process.

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Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.

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Length-limited variable-to-variable length codes for high-performance entropy coding

Cited by 4 publications

References 14 publications

Length-Limited Data Transformation and Compression

Length-Limited Data Transformation and Compression

Lower Bounds on the Redundancy of Huffman Codes With Known and Unknown Probabilities

A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression

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