Lossless medical image compression through lightweight binary arithmetic coding
Author
Bartrina Rapesta, JoanSanchez, Victor
Serra Sagrsità, Joan
Marcellin, Michael W.
Aulí Llinàs, Francesc
Blanes, Ian
Affiliation
Univ Arizona, Elect & Comp EngnIssue Date
2017-09-19
Metadata
Show full item recordPublisher
SPIE-INT SOC OPTICAL ENGINEERINGCitation
Joan Bartrina-Rapesta, Victor Sanchez, Joan Serra-Sagristà, Michael W. Marcellin, Francesc Aulí-Llinàs, Ian Blanes, "Lossless medical image compression through lightweight binary arithmetic coding", Proc. SPIE 10396, Applications of Digital Image Processing XL, 103960S (19 September 2017); doi: 10.1117/12.2273725; http://dx.doi.org/10.1117/12.2273725Rights
© 2017 SPIE.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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.ISSN
0277-786XEISSN
1996-756XVersion
Final published versionSponsors
Spanish Ministry of Economy and Competitiveness (MINECO); European Regional Development Fund (FEDER) [TIN2015-71126-R]; Catalan Government [2014SGR-691]; Centre National d'Etudes Spatiales (CNES)ae974a485f413a2113503eed53cd6c53
10.1117/12.2273725