A development of coordinate-based fuzzy encoding algorithm in compression of grayscale images

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dc.authoridZhu, Xiubin/0000-0002-7947-8749
dc.contributor.authorWang, Dan
dc.contributor.authorZhu, Xiubin
dc.contributor.authorPedrycz, Witold
dc.contributor.authorYu, Zhenhua
dc.contributor.authorLi, Zhiwu
dc.date.accessioned2024-05-19T14:42:38Z
dc.date.available2024-05-19T14:42:38Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractImage compression techniques realized in various ways have become an indispensable part in the practical storage and transmission of digital images. In this study, we present a novel method of lossy compression based on sampling and fuzzy encoding for grayscale images and discuss the problem of their reconstruction. First, an image is divided into a number of non-overlapping blocks of pixels. Next, we perform multiple rounds of random sampling. In each round, a number of pixels are selected as prototypes for the representing the corresponding block. Each pixel in the block is reconstructed based on the gray levels of the prototypes and membership degrees computed with respect to the distances of each pixel to the prototypes. The reconstruction abilities delivered by the prototypes are quantified by a certain objective fidelity criteria and the prototypes leading to lowest reconstruction error are determined as representatives of current block. Finally, once the representatives in each block have been determined, we reconstruct the whole image based on these prototypes. Experimental studies as well as visual evaluations show that the proposed algorithm is able to achieve high compression ratios while preserving the overall fidelity in the decompressed images.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [62076189, 62006184, 61873277]; Recruitment Program of Global Experts, Canada Research Chair (CRC); Natural Sciences and Engineering Research council of Canada (NSERC); Science and Technology Development Fund, MSAR [0012/2019/A3]en_US
dc.description.sponsorship& nbsp;This work was supported by the National Natural Science Foundation of China under Grant Nos. 62076189, 62006184, 61873277 the Recruitment Program of Global Experts, Canada Research Chair (CRC), Natural Sciences and Engineering Research council of Canada (NSERC) and the Science and Technology Development Fund, MSAR, under Grant No. 0012/2019/A3.en_US
dc.identifier.doi10.1007/s00500-023-09106-8
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.scopus2-s2.0-85168337735en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.1007/s00500-023-09106-8
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5265
dc.identifier.wosWOS:001051572400004en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectImage Compressionen_US
dc.subjectGrayscale Imageen_US
dc.subjectFuzzy Encodingen_US
dc.subjectCoordinated-Baseden_US
dc.titleA development of coordinate-based fuzzy encoding algorithm in compression of grayscale imagesen_US
dc.typeArticleen_US

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