Image processing using evolutive neural network

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

Division for Information Technology

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

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 language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Volume	6522
DOIs	https://doi.org/10.1117/12.723091
Publication status	Published - 2006
Event	Thirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics - Tomsk, Russian Federation Duration: 2 Jul 2006 → 7 Jul 2006

Other

Other	Thirteenth Joint International Symposium on Atmospheric and Ocean Optics/ Atmospheric Physics
Country	Russian Federation
City	Tomsk
Period	2.7.06 → 7.7.06

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Keywords

Adaptive image processing
Evolutive neural network
Genetic algorithm
Image enhancement

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

Cite this

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

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Access to Document

10.1117/12.723091