Wavelet filter adjusting for image lossless compression using pattern recognition

Oleksiy Pogrebnyak, Ignacio Hernández-Bautista, Oscar Camacho Nieto, Pablo Manrique Ramírez

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

2 Scopus citations

Abstract

A method for image lossless compression using lifting scheme wavelet transform is presented. The proposed method adjusts wavelet filter coefficients analyzing signal spectral characteristics to obtain a higher compression ratio in comparison to the standard CDF(2,2) and CDF(4,4) filters. The proposal is based on spectral pattern recognition with 1-NN classifier. Spectral patterns of a small fixed length are formed for the entire image permitting thus the global optimization of the filter coefficients, equal for all decompositions. The proposed method was applied to a set of test images obtaining better results in entropy values in comparison to the standard wavelet lifting filters.

Original languageEnglish
Title of host publicationPattern Recognition - 6th Mexican Conference, MCPR 2014, Proceedings
PublisherSpringer Verlag
Pages221-230
Number of pages10
ISBN (Print)9783319074900
DOIs
StatePublished - 2014
Event6th Mexican Conference on Pattern Recognition, MCPR 2014 - Cancun, Mexico
Duration: 25 Jun 201428 Jun 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8495 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Mexican Conference on Pattern Recognition, MCPR 2014
Country/TerritoryMexico
CityCancun
Period25/06/1428/06/14

Keywords

  • image compression
  • lifting scheme
  • pattern recognition
  • wavelets

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