Results 271 to 280 of about 937,847 (306)

Lossless and near-lossless image compression with color transformations

Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002
A comparison of lossless compression results is given for RGB, YC/sub R/C/sub B/ and reversible JPEG 2000 color space. The paper describes the general conditions that rounding errors of a color transformation do not cumulate in the consecutive cycles of forward and inverse transformation.
Marek Domanski, Krzysztof Rakowski
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Lossless-by-Lossy Coding for Scalable Lossless Image Compression

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2008
This paper presents a method of scalable lossless image compression by means of lossy coding. A progressive decoding capability and a full decoding for the lossless rendition are equipped with the losslessly encoded bit stream. Embedded coding is applied to large-amplitude coefficients in a wavelet transform domain.
Kazuma Shinoda, Hisakazu Kikuchi, Shogo Muramatsu   +2 more
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Evolutionary lossless compression with GP-ZIP

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
In recent research we proposed GP-zip, a system which uses evolution to find optimal ways to combine standard compression algorithms for the purpose of maximally losslessly compressing files and archives. The system divides files into blocks of predefined length.
Ahmed Kattan, Riccardo Poli
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Lossless Image Compression with BCTW

2006 International Conference on Image Processing, 2006
We present a new lossless image compression algorithm called BCTW, for bitplane context tree weighting, and a corresponding study into lossless image compression using several number representations and various algorithms. BCTW processes the image bitplane by bitplane and uses Context Tree Weighting (CTW) to estimate the probability of each pixel bit ...
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A Lossless Compression Algorithm for DNA sequences

International Journal of Bioinformatics Research and Applications, 2009
The increase of the amount of DNA sequences requires efficient computational algorithms for performing sequence comparison and analysis. Standard compression algorithms are not able to compress DNA sequences because they do not consider special characteristics of DNA sequences (i.e., DNA sequences contain several approximate repeats and complimentary ...
Taysir Hassan A. Soliman, Tarek F. Gharib, Alshaimaa Abo-Alian, Mohammed Alsharkawy   +3 more
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Lossless Compression of Digital Mammograms

2006
The file size of images generated using digital mammography systems varies between 8 MB and 50 MB. The amount of data to be stored in digital screening programs is huge. Image compression may be helpful. In this study 8491 digital and digitised mammography images are compressed using 14 lossless compression schemes. The results show that using lossless
R. Visser, L. Oostveen, Nico Karssemeijer   +2 more
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Visually Lossless HTML Compression

2009
The verbosity of the Hypertext Markup Language (HTML) remains one of its main weaknesses. This problem can be solved with the aid of HTML specialized compression algorithms. In this work, we describe a visually lossless HTML transform that, combined with generally used compression algorithms, allows to attain high compression ratios.
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Comprehensive Review on Lossy and Lossless Compression Techniques

Journal of The Institution of Engineers (India) Series B, 2021
S. Elakkiya, K. S. Thivya
semanticscholar   +1 more source

LZAC lossless data compression

Proceedings DCC 2002. Data Compression Conference, 2003
Summary form only given. This paper presents LZAC, a new universal lossless data compression algorithm derived from the popular and widely used LZ77 family. The objective of LZAC is to improve the compression ratios of the LZ77 family while still retaining the family's key characteristics: simple, universal and fast in decoding and economical in memory
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Lossless and Near-Lossless Compression for Mammographic Digital Images

2006 International Conference on Image Processing, 2006
In this paper, a method for lossless and near lossless compression of large digital mammograms is proposed. This method is based on a predictive coder that uses integer-to-integer operations, and generates a two-layer embedded bit stream (i.e. near-lossless and refinement layer). The maximum tolerated pixel distortion is guaranteed in the near lossless
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