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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/626487 |
| Date | 19 September 2017 |
| Creators | Bartrina Rapesta, Joan, Sanchez, Victor, Serra Sagrsità, Joan, Marcellin, Michael W., Aulí Llinàs, Francesc, Blanes, Ian |
| Contributors | Univ Arizona, Elect & Comp Engn |
| Publisher | SPIE-INT SOC OPTICAL ENGINEERING |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). |
| Relation | https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10396/2273725/Lossless-medical-image-compression-through-lightweight-binary-arithmetic-coding/10.1117/12.2273725.full |
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