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

2 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 languageEnglish (US)
Title of host publicationApplications of Digital Image Processing XL
PublisherSPIE
Volume10396
ISBN (Electronic)9781510612495
DOIs
StatePublished - Jan 1 2017
EventApplications of Digital Image Processing XL 2017 - San Diego, United States
Duration: Aug 7 2017Aug 10 2017

Other

OtherApplications of Digital Image Processing XL 2017
CountryUnited States
CitySan Diego
Period8/7/178/10/17

Fingerprint

Arithmetic Coding
Image Compression
Medical Image
coders
Image compression
coding
Binary
Lossless Compression
imagery
Normalization
Computational Cost
Costs
Coding
costs
Experimental Results
Context
Imagery

Keywords

  • 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

Cite this

Bartrina-Rapesta, J., Sanchez, V., Serra-Sagristà, J., Marcellin, M. W., Aulí-Llinàs, F., & Blanes, I. (2017). Lossless medical image compression through lightweight binary arithmetic coding. In Applications of Digital Image Processing XL (Vol. 10396). [103960S] SPIE. https://doi.org/10.1117/12.2273725

Lossless medical image compression through lightweight binary arithmetic coding. / Bartrina-Rapesta, Joan; Sanchez, Victor; Serra-Sagristà, Joan; Marcellin, Michael W; Aulí-Llinàs, Francesc; Blanes, Ian.

Applications of Digital Image Processing XL. Vol. 10396 SPIE, 2017. 103960S.

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

Bartrina-Rapesta, J, Sanchez, V, Serra-Sagristà, J, Marcellin, MW, Aulí-Llinàs, F & Blanes, I 2017, Lossless medical image compression through lightweight binary arithmetic coding. in Applications of Digital Image Processing XL. vol. 10396, 103960S, SPIE, Applications of Digital Image Processing XL 2017, San Diego, United States, 8/7/17. https://doi.org/10.1117/12.2273725
Bartrina-Rapesta J, Sanchez V, Serra-Sagristà J, Marcellin MW, Aulí-Llinàs F, Blanes I. Lossless medical image compression through lightweight binary arithmetic coding. In Applications of Digital Image Processing XL. Vol. 10396. SPIE. 2017. 103960S https://doi.org/10.1117/12.2273725
Bartrina-Rapesta, Joan ; Sanchez, Victor ; Serra-Sagristà, Joan ; Marcellin, Michael W ; Aulí-Llinàs, Francesc ; Blanes, Ian. / Lossless medical image compression through lightweight binary arithmetic coding. Applications of Digital Image Processing XL. Vol. 10396 SPIE, 2017.
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