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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationApplications of Digital Image Processing XL
EditorsAndrew G. Tescher
ISBN (Electronic)9781510612495
StatePublished - 2017
EventApplications of Digital Image Processing XL 2017 - San Diego, United States
Duration: Aug 7 2017Aug 10 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherApplications of Digital Image Processing XL 2017
Country/TerritoryUnited States
CitySan Diego


  • Arithmetic Coding
  • CCSDS-123
  • Lossless Coding
  • Medical Image Compression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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