A review of robust image enhancement algorithms and their applications

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dc.contributor.authorIrmak, E.
dc.contributor.authorErtas, A.H.
dc.date.accessioned2024-09-29T16:20:44Z
dc.date.available2024-09-29T16:20:44Z
dc.date.issued2016
dc.departmentKarabük Üniversitesien_US
dc.description4th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2016 -- 21 August 2016 through 24 August 2016 -- Oshawa -- 124272en_US
dc.description.abstractThe essential target of image enhancement is to minimize noise from a digital image by keeping the intrinsic information of the image preserved. The main difficulty in image enhancement is determining the criteria for enhancement and, therefore, more than one image enhancement techniques are empirical and require interactive procedures to obtain satisfactory results. In this paper robust image enhancement algorithms are discussed, implemented to noisy images and compared according to their robustness. The algorithms are especially able to improve the contrast of medical images, fingerprint images and selenography images by means of software techniques. When deciding that one image has better quality than another image, quality measure metrics are needed. Otherwise comparing image quality just by visual appearance may not be objective because images could vary from person to person. That is why quantitative metrics are crucial to compare images for their qualities. In this paper Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) quality measure metrics are used to compare the image enhancement methods systematically. All the methods are validated by the performance measures with PSNR and MSE. It is believed that this paper will provide comprehensive reference source for the researchers involved in image enhancement field. © 2016 IEEE.en_US
dc.identifier.doi10.1109/SEGE.2016.7589554
dc.identifier.endpage375en_US
dc.identifier.isbn978-150905111-3
dc.identifier.scopus2-s2.0-84995679038en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage371en_US
dc.identifier.urihttps://doi.org/10.1109/SEGE.2016.7589554
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9287
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2016 4th IEEE International Conference on Smart Energy Grid Engineering, SEGE 2016en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfuzzy set theoryen_US
dc.subjecthistogram equalizationen_US
dc.subjecthistogram matchingen_US
dc.subjectimage enhancement algorithmen_US
dc.titleA review of robust image enhancement algorithms and their applicationsen_US
dc.typeConference Objecten_US

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