Image compression algorithm based on morphological associative memories

Enrique Guzmán, Oleksiy Pogrebnyak, Cornelio Yáñez, José A. Moreno

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

11 Scopus citations

Abstract

A new method for image compression based on Morphological Associative Memories (MAM) is proposed. We used MAM at the transformation stage of image coding, thereby replacing the traditional methods such as Discrete Cosine Transform or Wavelet Transform. After applying the MAM, the informative image data are concentrated in a minimum of values. The next stages of image coding can be obtained by taking advantage of this new representation of the image. The main advantage offered by the MAM with respect to the traditional methods is the speed of processing, whereas the compression rate and the obtained signal to noise ratios compete with the traditional methods.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 11th Iberoamerican Congress in Pattern Recognition, CIARP 2006, Proceedings
PublisherSpringer Verlag
Pages519-528
Number of pages10
ISBN (Print)3540465561, 9783540465560
DOIs
StatePublished - 2006
Event11th Iberoamerican Congress in Pattern Recognition, CIARP 2006 - Cancun, Mexico
Duration: 14 Nov 200617 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4225 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Iberoamerican Congress in Pattern Recognition, CIARP 2006
Country/TerritoryMexico
CityCancun
Period14/11/0617/11/06

Keywords

  • Image compression
  • Morphological associative memories
  • Morphological hetroassociative memories min

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