Efficient image compression based on error value centralization by sign bits

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

Abstract

In the last two decades, there exist many high-performance prediction-based methods that use different coefficients of causal neighbors in order to exploit the relationship of spatial energy to produce a less error image. Besides, more and more researches focus on the accuracy of predictor; nevertheless, the predictor spends a lot of time on finding the best coefficients of causal neighbors. The objective of our research is to propose an efficient and implementable method to improve compression ratio, without increasing extra computation complexity. Here, we present an improved lossless image compression based on the prediction method, by the proposed application of efficient error value centralization by sign bits. The contribution of this paper is to centralize error values in a novel way to improves coding performance. Experimental results show that our proposed method achieves higher compression ratio than the context-based, adaptive, and lossless image codec (CALIC) method for the images with many details or slightly regular texture.

Original languageEnglish
Title of host publication2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Conference Proceedings
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013 - Xi'an, Shaanxi, China
Duration: 2013 Oct 222013 Oct 25

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Other

Other2013 IEEE International Conference of IEEE Region 10, IEEE TENCON 2013
CountryChina
CityXi'an, Shaanxi
Period13-10-2213-10-25

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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