A study of bias correction methods for enhancing median edge detector prediction

Haijiang Tang, Sei Ichiro Kamata, Kazuyuki Tsuneyoshi

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

Abstract

In this paper, we present three novel lossless compression approaches for gray-scale continuous tone natural image. Our methods enhance the median edge detector (MED), which is the core part of JPED-LS algorithm, by reducing the entropy of the prediction error via adaptive regression. These modified predictors improve the prediction accuracy by reducing the negative effect due to MED's oversimplified edge orientation detection. The experimental results show that our approaches achieve evidently better performance than MED with only neglectable increasing of computational complexity and without introduce extra pixels into the causal template.

Original languageEnglish
Title of host publication2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005
DOIs
Publication statusPublished - 2006 Dec 1
Event2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005 - Shanghai, China
Duration: 2005 Oct 302005 Nov 2

Publication series

Name2005 IEEE 7th Workshop on Multimedia Signal Processing

Conference

Conference2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005
CountryChina
CityShanghai
Period05/10/3005/11/2

Keywords

  • Bias correction
  • Lossless image compression
  • Predictive coding

ASJC Scopus subject areas

  • Signal Processing

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  • Cite this

    Tang, H., Kamata, S. I., & Tsuneyoshi, K. (2006). A study of bias correction methods for enhancing median edge detector prediction. In 2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005 [4014035] (2005 IEEE 7th Workshop on Multimedia Signal Processing). https://doi.org/10.1109/MMSP.2005.248614