Geodesic
Image contrast improvement method using genetic algorithm
Informacionnye tehnologii i vyčislitelnye sistemy, no. 2 (2023), pp. 67-75 Cet article a éte moissonné depuis la source Math-Net.Ru

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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.
Mots-clés : image, pixel
Keywords: preprocessing, brightness, contrast, quality, neighborhood, genetic algorithm, quality assessment criteria. 
@article{ITVS_2023_2_a6,
     author = {V. N. Gridin and K. I. Domanov and V. I. Solodovnikov},
     title = {Image contrast improvement method using genetic algorithm},
     journal = {Informacionnye tehnologii i vy\v{c}islitelnye sistemy},
     pages = {67--75},
     year = {2023},
     number = {2},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ITVS_2023_2_a6/}
}
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V. N. Gridin; K. I. Domanov; V. I. Solodovnikov. Image contrast improvement method using genetic algorithm. Informacionnye tehnologii i vyčislitelnye sistemy, no. 2 (2023), pp. 67-75. http://geodesic.mathdoc.fr/item/ITVS_2023_2_a6/