Lossless medical image compression through lightweight binary arithmetic coding
| dc.contributor.author | Bartrina Rapesta, Joan | |
| dc.contributor.author | Sanchez, Victor | |
| dc.contributor.author | Serra Sagrsità, Joan | |
| dc.contributor.author | Marcellin, Michael W. | |
| dc.contributor.author | Aulí Llinàs, Francesc | |
| dc.contributor.author | Blanes, Ian | |
| dc.date.accessioned | 2018-01-31T18:53:44Z | |
| dc.date.available | 2018-01-31T18:53:44Z | |
| dc.date.issued | 2017-09-19 | |
| dc.identifier.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 | en |
| dc.identifier.issn | 0277-786X | |
| dc.identifier.doi | 10.1117/12.2273725 | |
| dc.identifier.uri | http://hdl.handle.net/10150/626487 | |
| dc.description.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. | |
| dc.description.sponsorship | 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) | en |
| dc.language.iso | en | en |
| dc.publisher | SPIE-INT SOC OPTICAL ENGINEERING | en |
| dc.relation.url | https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10396/2273725/Lossless-medical-image-compression-through-lightweight-binary-arithmetic-coding/10.1117/12.2273725.full | en |
| dc.rights | © 2017 SPIE. | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.subject | Medical Image Compression | en |
| dc.subject | CCSDS-123 | en |
| dc.subject | Lossless Coding | en |
| dc.subject | Arithmetic Coding | en |
| dc.title | Lossless medical image compression through lightweight binary arithmetic coding | en |
| dc.type | Article | en |
| dc.identifier.eissn | 1996-756X | |
| dc.contributor.department | Univ Arizona, Elect & Comp Engn | en |
| dc.identifier.journal | APPLICATIONS OF DIGITAL IMAGE PROCESSING XL | en |
| dc.description.collectioninformation | 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. | en |
| dc.eprint.version | Final published version | en |
| refterms.dateFOA | 2018-06-16T21:00:06Z | |
| html.description.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. |
