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Code and parse trees for lossless source encoding
 Communications in Information and Systems
, 2001
"... This paper surveys the theoretical literature on fixedtovariablelength lossless source code trees, called code trees, and on variablelengthtofixed lossless sounce code trees, called parse trees. Huffman coding [ l] is the most well known code tree problem, but there are a number of interestin ..."
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Cited by 63 (1 self)
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This paper surveys the theoretical literature on fixedtovariablelength lossless source code trees, called code trees, and on variablelengthtofixed lossless sounce code trees, called parse trees. Huffman coding [ l] is the most well known code tree problem, but there are a number of interesting variants of the problem formulation which lead to other combinatorial optimization problems. Huffman coding as an
The Design and Analysis of Efficient Lossless Data Compression Systems
, 1993
"... Our thesis is that high compression efficiency for text and images can be obtained by using sophisticated statistical compression techniques, and that greatly increased speed can be achieved at only a small cost in compression efficiency. Our emphasis is on elegant design and mathematical as well as ..."
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Cited by 59 (0 self)
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Our thesis is that high compression efficiency for text and images can be obtained by using sophisticated statistical compression techniques, and that greatly increased speed can be achieved at only a small cost in compression efficiency. Our emphasis is on elegant design and mathematical as well as empirical analysis. We analyze arithmetic coding as it is commonly implemented and show rigorously that almost no compression is lost in the implementation. We show that highefficiency lossless compression of both text and grayscale images can be obtained by using appropriate models in conjunction with arithmetic coding. We introduce a fourcomponent paradigm for lossless image compression and present two methods that give state of the art compression efficiency. In the text compression area, we give a small improvement on the preferred method in the literature. We show that we can often obtain significantly improved throughput at the cost of slightly reduced compression. The extra speed c...
Analysis of Arithmetic Coding for Data Compression
 INFORMATION PROCESSING AND MANAGEMENT
, 1992
"... Arithmetic coding, in conjunction with a suitable probabilistic model, can provide nearly optimal data compression. In this article we analyze the effect that the model and the particular implementation of arithmetic coding have on the code length obtained. Periodic scaling is often used in arithmet ..."
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Cited by 43 (6 self)
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Arithmetic coding, in conjunction with a suitable probabilistic model, can provide nearly optimal data compression. In this article we analyze the effect that the model and the particular implementation of arithmetic coding have on the code length obtained. Periodic scaling is often used in arithmetic coding implementations to reduce time and storage requirements; it also introduces a recency effect which can further affect compression. Our main contribution is introducing the concept of weighted entropy and using it to characterize in an elegant way the effect that periodic scaling has on the code length. We explain why and by how much scaling increases the code length for files with a homogeneous distribution of symbols, and we characterize the reduction in code length due to scaling for files exhibiting locality of reference. We also give a rigorous proof that the coding effects of rounding scaled weights, using integer arithmetic, and encoding endoffile are negligible.