New error criterion for near-lossless image compression

Nasir Memon, Nader Moayeri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new criterion for near-lossless image compression and compares it with the more familiar maximum pixel error criterion in terms of compression performance and coded image subjective quality. In this new framework we compress an image in such a way that at each pixel the total error between the original and the coded images over a W×W window around the pixel does not exceed ε in magnitude. The new criterion's main advantage is that it preserves image brightness and color. The compression scheme used in this work is similar to a trellis-searched scheme proposed by Ke and Marcellin in that our scheme is also a predictive, context-based scheme. However, the search for an optimal path, representing a set of reconstruction values for an image row that satisfies the error criterion and yields the minimum bit rate, has to be done in a planar directed graph instead of a trellis. We show that this framework is also applicable to a joint image filtering and compression scenario. We present simulation results showing the performance of the new error criterion and compare it with the maximum pixel error criterion.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE Comp Soc
Pages662-665
Number of pages4
Volume3
StatePublished - 1997
EventProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA
Duration: Oct 26 1997Oct 29 1997

Other

OtherProceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
CitySanta Barbara, CA, USA
Period10/26/9710/29/97

    Fingerprint

ASJC Scopus subject areas

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

Cite this

Memon, N., & Moayeri, N. (1997). New error criterion for near-lossless image compression. In IEEE International Conference on Image Processing (Vol. 3, pp. 662-665). IEEE Comp Soc.