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

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

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.

Original languageAmerican English
JournalProceedings of SPIE - The International Society for Optical Engineering
DOIs
Publication statusPublished - 2017

Keywords

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

Fingerprint Dive into the research topics of 'Lossless medical image compression through lightweight binary arithmetic coding'. Together they form a unique fingerprint.

Cite this