Near-lossless image compression: minimum-entropy, constrained-error DPCM

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Abstract

A near-lossless image compression scheme is presented. It is essentially a DPCM system with a mechanism incorporated to minimize the entropy of the quantized prediction error sequence. With a 'near-lossless' criterion of no more than a d gray level error for each pixel, where d is a small non-negative integer, trellises describing all allowable quantized prediction error sequences are constructed. A set of 'contexts' is defined for the conditioning prediction error model and an algorithm that produces minimum entropy conditioned on the contexts is presented. Finally, experimental results are given.

Original languageEnglish (US)
Pages298-301
Number of pages4
StatePublished - Jan 1 1996
EventProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) - Washington, DC, USA
Duration: Oct 23 1995Oct 26 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3)
CityWashington, DC, USA
Period10/23/9510/26/95

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ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

Cite this

Ke, L., & Marcellin, M. W. (1996). Near-lossless image compression: minimum-entropy, constrained-error DPCM. 298-301. Paper presented at Proceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3), Washington, DC, USA, .