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    Lossless medical image compression through lightweight binary arithmetic coding

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    103960S.pdf
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    Final Published Version
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    Author
    Bartrina Rapesta, Joan
    Sanchez, Victor
    Serra Sagrsità, Joan
    Marcellin, Michael W.
    Aulí Llinàs, Francesc
    Blanes, Ian
    Affiliation
    Univ Arizona, Elect & Comp Engn
    Issue Date
    2017-09-19
    Keywords
    Medical Image Compression
    CCSDS-123
    Lossless Coding
    Arithmetic Coding
    
    Metadata
    Show full item record
    Publisher
    SPIE-INT SOC OPTICAL ENGINEERING
    Citation
    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/10.1117/12.2273725
    Journal
    APPLICATIONS OF DIGITAL IMAGE PROCESSING XL
    Rights
    © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (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
    0277-786X
    EISSN
    1996-756X
    DOI
    10.1117/12.2273725
    Version
    Final published version
    Sponsors
    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)
    Additional Links
    https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10396/2273725/Lossless-medical-image-compression-through-lightweight-binary-arithmetic-coding/10.1117/12.2273725.full
    ae974a485f413a2113503eed53cd6c53
    10.1117/12.2273725
    Scopus Count
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    UA Faculty Publications

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