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Lossless medical image compression through lightweight binary arithmetic coding
Author(s): Joan Bartrina-Rapesta; Victor Sanchez; Joan Serra-Sagristà; Michael W. Marcellin; Francesc Aulí-Llinàs; Ian Blanes
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Paper 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.

Paper Details

Date Published: 19 September 2017
PDF: 9 pages
Proc. SPIE 10396, Applications of Digital Image Processing XL, 103960S (19 September 2017); doi: 10.1117/12.2273725
Show Author Affiliations
Joan Bartrina-Rapesta, Univ. Autònoma de Barcelona (Spain)
Victor Sanchez, The Univ. of Warwick (United Kingdom)
Joan Serra-Sagristà, Univ. Autònoma de Barcelona (Spain)
Michael W. Marcellin, The Univ. of Arizona (United States)
Francesc Aulí-Llinàs, Univ. Autònoma de Barcelona (Spain)
Ian Blanes, Univ. Autònoma de Barcelona (Spain)


Published in SPIE Proceedings Vol. 10396:
Applications of Digital Image Processing XL
Andrew G. Tescher, Editor(s)

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