Abstract
We propose a context-based, adaptive, lossless image codec (CALIC). CALIC obtains higher lossless compression of continuous-tone images than other techniques reported in the literature. This high coding efficiency is accomplished with relatively low time and space complexities. CALIC puts heavy emphasis on image data modeling. A unique feature of CALIC is the use of a large number of modeling contexts to condition a non-linear predictor and make it adaptive to varying source statistics. The non-linear predictor adapts via an error feedback mechanism. In this adaptation process, CALIC only estimates the expectation of prediction errors conditioned on a large number of contexts rather than estimating a large number of conditional error probabilities. The former estimation technique can afford a large number of modeling contexts without suffering from the sparse context problem. The low time and space complexities of CALIC are attributed to efficient techniques for forming and quantizing modeling contexts.
| Original language | English (US) |
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| Title of host publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Publisher | IEEE |
| Pages | 1890-1893 |
| Number of pages | 4 |
| Volume | 4 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA Duration: May 7 1996 → May 10 1996 |
Other
| Other | Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) |
|---|---|
| City | Atlanta, GA, USA |
| Period | 5/7/96 → 5/10/96 |
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Acoustics and Ultrasonics