Modeling and low-complexity adaptive coding for image prediction residuals
- 24 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 353-356 vol.2
- https://doi.org/10.1109/icip.1996.560829
Abstract
This paper elaborates on the use of discrete, two-sided geometric distribution models for image prediction residuals. After providing achievable bounds for universal coding of a rich family of models, which includes traditional image models, we present a new family of practical prefix codes for adaptive image compression. This family is optimal for two-sided geometric distributions and is an extension of the Golomb (1966) codes. Our new family of codes allows for encoding of prediction residuals at a complexity similar to that of Golomb codes, without recourse to the rough approximations used when a code designed for non-negative integers is matched to the encoding of any integer. We also provide adaptation criteria for a further simplified, sub-optimal family of codes used in practice.Keywords
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