Medical Image Enhancement using Guided Filtering and Chaotic Inertia Weight Black Hole Algorithm

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dc.authorscopusid57194619312
dc.contributor.authorPashaei, Elham
dc.date.accessioned2024-09-11T19:59:02Z
dc.date.available2024-09-11T19:59:02Z
dc.date.issued2021
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description5h International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2021 -- 21 October 2021 through 23 October 2021 -- Ankara -- 174473en_US
dc.description.abstractIn this study, a new hybrid approach is suggested for medical image enhancement. The main idea is based on the hybrid of the guided filter and chaotic inertia weight black hole algorithm (GFCBH) to enhance and highlight the image information using a new objective function. GFCBH is a two-stage approach that, first, applies the guided filter to the input image which performs as an edge-preserving smoothing operator, and then, uses the CBH algorithm to automatically find optimal parameters for transformation function based on the objective function. In the proposed objective function, universal image quality index (Q), entropy, edge pixels, and gray level cooccurrence matrix (GLCM) based contrast and energy are considered to achieve the best-enhanced image. The experimental results are verified by comparison with ten well-known image enhancement techniques using entropy and peak signal-to-noise-ratio (PSNR) measurement criteria. The extensive experiments along with qualitative and quantitative evaluations show that the suggested method can successfully enhance images and performs better than most state-of-art techniques. © 2021 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT52890.2021.9604701
dc.identifier.endpage42en_US
dc.identifier.isbn978-166544930-4en_US
dc.identifier.scopus2-s2.0-85123271977en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage37en_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT52890.2021.9604701
dc.identifier.urihttps://hdl.handle.net/11363/8619
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISMSIT 2021 - 5th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectchaotic inertia weight black hole optimization algorithm; guided filtering; histogram equalization; medical image enhancement; PSNRen_US
dc.titleMedical Image Enhancement using Guided Filtering and Chaotic Inertia Weight Black Hole Algorithmen_US
dc.typeConference Objecten_US

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