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Computer Optics, 2022, Volume 46, Issue 1, Pages 113–120
DOI: https://doi.org/10.18287/2412-6179-CO-911
(Mi co999)
 

IMAGE PROCESSING, PATTERN RECOGNITION

wEscore: quality assessment method of multichannel image visualization with regard to angular resolution

D. S. Sidorchuk

Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow
Abstract: This 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 assess-ment 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.
Keywords: hyperspectral image visualization, decolorization, Escore, local contrast
Received: 19.04.2021
Accepted: 22.07.2021
Document Type: Article
Language: English
Citation: D. S. Sidorchuk, “wEscore: quality assessment method of multichannel image visualization with regard to angular resolution”, Computer Optics, 46:1 (2022), 113–120
Citation in format AMSBIB
\Bibitem{Sid22}
\by D.~S.~Sidorchuk
\paper wEscore: quality assessment method of multichannel image visualization with regard to angular resolution
\jour Computer Optics
\yr 2022
\vol 46
\issue 1
\pages 113--120
\mathnet{http://mi.mathnet.ru/co999}
\crossref{https://doi.org/10.18287/2412-6179-CO-911}
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