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Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2023, Issue 2, Pages 67–75
DOI: https://doi.org/10.14357/20718632230207
(Mi itvs810)
 

INTELLIGENT SYSTEMS AND TECHNOLOGIES

Image contrast improvement method using genetic algorithm

V. N. Gridin, K. I. Domanov, V. I. Solodovnikov

Design Information Technologies Center Russian Academy of Sciences, Odintsovo, Moscow Region, Russian Federation
Abstract: The paper presents a method for local image contrast enhancement based on the distribution of gray levels in the vicinity of each individual pixel. The considered approach was automated using a genetic algorithm, which made it possible to eliminate the need for manual adjustment of the transformation parameters. The necessary criteria for assessing the quality of images are selected, among which the main ones are: the number of edge pixels, their total intensity, the measure of image entropy and the measure of brightness adaptation. Software components have been implemented and their functioning has been tested on various classes of images, which has shown the success of this approach for images with a high density of distribution of gradations of brightness, uniform illumination and a weak gradient of boundary pixels.
Keywords: image, preprocessing, brightness, contrast, quality, pixel, neighborhood, genetic algorithm, quality assessment criteria.
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. N. Gridin, K. I. Domanov, V. I. Solodovnikov, “Image contrast improvement method using genetic algorithm”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2023, no. 2, 67–75
Citation in format AMSBIB
\Bibitem{GriDomSol23}
\by V.~N.~Gridin, K.~I.~Domanov, V.~I.~Solodovnikov
\paper Image contrast improvement method using genetic algorithm
\jour Informatsionnye Tekhnologii i Vychslitel'nye Sistemy
\yr 2023
\issue 2
\pages 67--75
\mathnet{http://mi.mathnet.ru/itvs810}
\crossref{https://doi.org/10.14357/20718632230207}
\elib{https://elibrary.ru/item.asp?id=54070988}
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