1 April 2010 Efficient adaptive arithmetic coding based on updated probability distribution for lossless image compression
Atef Masmoudi, William Puech, Mohamed Salim Bouhlel
Author Affiliations +
Abstract
We propose an efficient lossless compression scheme for still images based on arithmetic coding. The scheme presents a novel adaptive arithmetic coding that updates the probabilities of pixels only after detecting the last occurrence of each pixel and then removes the redundancy from the original image effectively. The proposed approach has interestingly low computational complexity. In addition, unlike other statistical coding techniques, arithmetic coding in the proposed scheme is not solely dependent on the pixel probability distribution but also on the image block sorting. The proposed method is compared to both static and adaptive order-0 models while taking into account compression ratios and processing time. Experimental results, based on a set of 100 gray-level images, demonstrate that the proposed scheme gives mean compression ratios that are 5.5% higher than those by the conventional arithmetic encoders as well as significantly faster than the order-0 adaptive arithmetic coding.
©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Atef Masmoudi, William Puech, and Mohamed Salim Bouhlel "Efficient adaptive arithmetic coding based on updated probability distribution for lossless image compression," Journal of Electronic Imaging 19(2), 023014 (1 April 2010). https://doi.org/10.1117/1.3435341
Published: 1 April 2010
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CITATIONS
Cited by 19 scholarly publications.
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KEYWORDS
Image compression

Computer programming

Image processing

Binary data

Algorithm development

Biotechnology

Data compression

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