From Event: SPIE Optical Engineering + Applications, 2017
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.
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 (Presented at SPIE Optical Engineering + Applications: August 08, 2017; Published: 19 September 2017); https://doi.org/10.1117/12.2273725.
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