Research of neighborhood searching fractal image coding algorithm based on Ant Colony Optimization

Li Lou, Yong Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A kind of fractal improved coding algorithms based on Ant Colony Optimization and neighborhood search matching way is presented in this paper. The compression ratio of this algorithm is higher than that of Jacquin's as well as the coding speed is faster than that of Jacquin's on the premise of similar signal-to-noise ratio. Experimental results show that the compression ratio of this neighborhood searching fractal image coding algorithm based on ant colony optimization can reach to 14.33, the PSNR can reach to 29.7dB, encoding time decreases to 120s and decoding time is 28s.

Original languageEnglish
Title of host publicationIntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages761-764
Number of pages4
ISBN (Electronic)9781467376068
DOIs
StatePublished - 18 Dec 2015
EventSAI Intelligent Systems Conference, IntelliSys 2015 - London, United Kingdom
Duration: 10 Nov 201511 Nov 2015

Publication series

NameIntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference

Conference

ConferenceSAI Intelligent Systems Conference, IntelliSys 2015
Country/TerritoryUnited Kingdom
CityLondon
Period10/11/1511/11/15

Keywords

  • Ant Colony Optimization
  • Fractal Coding
  • Neighborhood
  • Range Block

Fingerprint

Dive into the research topics of 'Research of neighborhood searching fractal image coding algorithm based on Ant Colony Optimization'. Together they form a unique fingerprint.

Cite this