A multi-scan adaptive linear prediction approach for lossless image compression

Haijiang Tang, Seiichiro Kamata, Masa Aki Kobayashi

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

Abstract

This paper presents a block based lossless compression approach for gray scale images. Multiple scanning methods are applied to each block, and a newly proposed adaptive linear prediction is performed. There are different prediction residuals obtained corresponding to different context based on multiple scanning. We choose the best residual for coding. That is, rather than relying any single scanning, our approach is to select a scanning produces the best result on each black. The prediction coefficients are updated during the scanning to optimize the coding accuracy. Experiment results show that our method out-performed JPEG-LS 4-5% in compression efficiency.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages3004-3009
Number of pages6
Volume3
DOIs
Publication statusPublished - 2004
Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague
Duration: 2004 Oct 102004 Oct 13

Other

Other2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
CityThe Hague
Period04/10/1004/10/13

    Fingerprint

Keywords

  • Adaptive linear prediction
  • Lossless compression
  • Multi-scan

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Tang, H., Kamata, S., & Kobayashi, M. A. (2004). A multi-scan adaptive linear prediction approach for lossless image compression. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (Vol. 3, pp. 3004-3009) https://doi.org/10.1109/ICSMC.2004.1400791