Binary Image Coding using Cellular Neural Networks

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

  • Dirk Feiden - , Goethe University Frankfurt a.M. (Author)
  • Ronald Tetzlaff - , Goethe University Frankfurt a.M. (Author)

Abstract

Image coding still is an important research field in image processing. Although storage capacities increase permanently, image file sizes are of high interest in the area of image transmission. E.g. in the Internet the number of bytes transmitted is directly correlated to the costs and the time consumption for the transmission. Furthermore, because of the extremely high amount of data, in video processing efficient compression methods are always point of interest. In this contribution a new approach of image coding is presented, which uses the relatively new paradigm of Cellular Neural Networks (CNN). CNN are massively parallel computing arrays, which are perfectly suited for high speed image processing. Furthermore, their robustness is another outstanding feature of CNN hardware implementations, so that they predominate many other neural network implementations.

Details

Original languageEnglish
Pages1149-1152
Number of pages4
Publication statusPublished - 2003
Peer-reviewedYes
Externally publishedYes

Conference

TitleInternational Joint Conference on Neural Networks 2003
Duration20 - 24 July 2003
CityPortland, OR
CountryUnited States of America

External IDs

ORCID /0000-0001-7436-0103/work/173513945

Keywords

ASJC Scopus subject areas