Image processing using evolutive neural network

Alexander V. Chernyavsky, Vladimir G. Spitsyn, Yuri R. Tsoy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

The paper present a neuroevolutionary method of monochrome and color images enhancement. The proposed method is based on local-adaptive approach to image processing. Neural network is tuned to perform enhancement of particular image using genetic algorithm with use of the generalized image evaluation criterion that relies on the contrast degree of the processed image.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume6522
DOIs
Publication statusPublished - 2006
EventThirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics - Tomsk, Russian Federation
Duration: 2 Jul 2006 → 7 Jul 2006

Other

OtherThirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics
CountryRussian Federation
CityTomsk
Period2.7.06 → 7.7.06

Keywords

  • Adaptive image processing
  • Evolutive neural network
  • Genetic algorithm
  • Image enhancement

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

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    Chernyavsky, A. V., Spitsyn, V. G., & Tsoy, Y. R. (2006). Image processing using evolutive neural network. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6522). [652211] https://doi.org/10.1117/12.723091