Lossless medical image compression through lightweight binary arithmetic coding

Joan Bartrina-Rapesta; Victor Sanchez; Joan Serra-Sagristà; Michael W. Marcellin; Francesc Aulí-Llinàs; Ian Blanes

doi:10.1117/12.2273725

19 September 2017 Lossless medical image compression through lightweight binary arithmetic coding

Joan Bartrina-Rapesta, Victor Sanchez, Joan Serra-Sagristà, Michael W. Marcellin, Francesc Aulí-Llinàs, Ian Blanes

Author Affiliations +

Proceedings Volume 10396, Applications of Digital Image Processing XL; 103960S (2017) https://doi.org/10.1117/12.2273725
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

Abstract

A contextual lightweight arithmetic coder is proposed for lossless compression of medical imagery. Context definition uses causal data from previous symbols coded, an inexpensive yet efficient approach. To further reduce the computational cost, a binary arithmetic coder with fixed-length codewords is adopted, thus avoiding the normalization procedure common in most implementations, and the probability of each context is estimated through bitwise operations. Experimental results are provided for several medical images and compared against state-of-the-art coding techniques, yielding on average improvements between nearly 0.1 and 0.2 bps.

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Citation Download Citation

Joan Bartrina-Rapesta, Victor Sanchez, Joan Serra-Sagristà, Michael W. Marcellin, Francesc Aulí-Llinàs, and Ian Blanes "Lossless medical image compression through lightweight binary arithmetic coding", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103960S (19 September 2017); https://doi.org/10.1117/12.2273725

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