Отрывок: Examples of color images with corresponding sets of annotated visualizations are shown in fig. 2 – 7. markup is specified as red and green circles on grayscale images: red circles correspond to visualizations with per- ceived lost contrasts, and green circles correspond to visu- alizations with perceived preserved contrasts. The conditions for image observation during the markup process were as follows:...
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dc.contributor.authorSidorchuk, D.S.-
dc.date.accessioned2022-03-10 15:35:27-
dc.date.available2022-03-10 15:35:27-
dc.date.issued2022-01-
dc.identifierDspace\SGAU\20220305\96074ru
dc.identifier.citationSidorchuk DS. wEscore: quality assessment method of multichannel image visualization with regard to angular resolution. Computer Optics 2022; 46(1): 113-120. DOI: 10.18287/2412-6179-CO-911.ru
dc.identifier.uri10.18287/2412-6179-CO-911-
dc.identifier.urihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/wEscore-quality-assessment-method-of-multichannel-image-visualization-with-regard-to-angular-resolution-96074-
dc.description.abstractThis work considers the problem of quality assessment of multichannel image visualization methods. One approach to such an assessment, the Escore quality measure, is studied. This measure, initially proposed for decolorization methods evaluation, can be generalized for the assessment of hyperspectral image visualization methods. It is shown that Escore does not account for the loss of local contrast at the supra-pixel scale. The sensitivity to the latter in humans depends on the observation conditions, so we propose a modified wEscore measure which includes the parameters allowing for the adjustment of the local contrast scale based on the angular resolution of the images. We also describe the adjustment of wEscore parameters for the evaluation of known decolorization algorithms applied to the images from the COLOR250 and the Cadik datasets with given observational conditions. When ranking the results of these algorithms and comparing it to the ranking based on human perception, wEscore turned out to be more accurate than Escore.ru
dc.description.sponsorshipThis work was supported by Russian Science Foundation (Project No. 20-61-47089).ru
dc.language.isoenru
dc.publisherСамарский национальный исследовательский университетru
dc.relation.ispartofseries46;1-
dc.subjecthyperspectral image visualization, decolorization, Escore, local contrastru
dc.titlewEscore: quality assessment method of multichannel image visualization with regard to angular resolutionru
dc.typeArticleru
dc.textpartExamples of color images with corresponding sets of annotated visualizations are shown in fig. 2 – 7. markup is specified as red and green circles on grayscale images: red circles correspond to visualizations with per- ceived lost contrasts, and green circles correspond to visu- alizations with perceived preserved contrasts. The conditions for image observation during the markup process were as follows:...-
dc.classindex.scsti28.17.33-
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