Lossless medical image compression through lightweight binary arithmetic coding
AuthorBartrina Rapesta, Joan
Serra Sagrsità, Joan
Marcellin, Michael W.
Aulí Llinàs, Francesc
AffiliationUniv Arizona, Elect & Comp Engn
MetadataShow full item record
PublisherSPIE-INT SOC OPTICAL ENGINEERING
CitationJoan 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/10.1117/12.2273725
Rights© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Collection InformationThis 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 email@example.com.
AbstractA 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.
VersionFinal published version
SponsorsSpanish Ministry of Economy and Competitiveness (MINECO); European Regional Development Fund (FEDER) [TIN2015-71126-R]; Catalan Government [2014SGR-691]; Centre National d'Etudes Spatiales (CNES)