Restoration of degraded images using genetic programming

José Enrique Hernández-Beltrán, Víctor H. Díaz-Ramírez, Leonardo Trujillo, Pierrick Legrand

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

2 Scopus citations

Abstract

In image restoration problems it is commonly assumed that image degradations are linear. In real-life this assumption is not always satisfied causing linear restoration methods fail. In this work, we present the design of an image restoration filtering based on genetic programming. The proposed filtering is given by a secuence of basic mathematical operators that allows to retrieve an undegraded image from an image degraded with noise. Computer simulations results obtained with the proposed algorithm in terms of objective metrics are analyzed and discussed by processing images degraded with noise. The obtained results are compared with those obtained with existing linear filters.

Original languageEnglish
Title of host publicationOptics and Photonics for Information Processing X
EditorsKhan M. Iftekharuddin, Andres Marquez, Mohammad A. Matin, Abdul A. S. Awwal, Mireya Garcia Vazquez
PublisherSPIE
ISBN (Electronic)9781510603318
DOIs
StatePublished - 2016
Event10th Conference on Optics and Photonics for Information Processing - San Diego, United States
Duration: 29 Aug 201630 Aug 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9970
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference10th Conference on Optics and Photonics for Information Processing
Country/TerritoryUnited States
CitySan Diego
Period29/08/1630/08/16

Keywords

  • Genetic Programming
  • image restoration
  • non-linear filters

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