Lossless image coding via adaptive Takagi-Sugeno fuzzy neural network predictor

Ching Hung Lee*, Wei Yu Lai, Chih Chang Chen

*Corresponding author for this work

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

1 Scopus citations

Abstract

With the improvement of the digital system and the development of the internet, the quality of the multimedia data which includes image, voice and video becomes more and more, so the data compression becomes important. This paper proposed an adaptive Takagi-Sugeno fuzzy neural network (TFNN) system on the data compression technology. The TFNN is applied to be a predictor for differential pulse code modulation (DPCM) of images compression. The TFNN predictor can not only have accurate prediction, but also rather study and adapt to various and constant changing data A through comparison with the most advanced methods in the literatures highlight the advantages of the proposed adaptive TFNN scheme to data compression.

Original languageEnglish
Title of host publicationConference Proceedings - 2004 IEEE International Conference on Networking, Sensing and Control
Pages565-570
Number of pages6
StatePublished - 2004
EventConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control - Taipei, Taiwan
Duration: 21 Mar 200423 Mar 2004

Publication series

NameConference Proceeding - IEEE International Conference on Networking, Sensing and Control
Volume1

Conference

ConferenceConference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
CountryTaiwan
CityTaipei
Period21/03/0423/03/04

Keywords

  • Back-propagation learning algorithm
  • Image compression
  • Lossless image coding
  • Predictor differenttial pulse code modulation
  • T-S Fuzzy Model

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    Lee, C. H., Lai, W. Y., & Chen, C. C. (2004). Lossless image coding via adaptive Takagi-Sugeno fuzzy neural network predictor. In Conference Proceedings - 2004 IEEE International Conference on Networking, Sensing and Control (pp. 565-570). (Conference Proceeding - IEEE International Conference on Networking, Sensing and Control; Vol. 1).