Lossy hyperspectral image compression based on intraband prediction and inter-band fractal

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dc.contributor.authorAli, Bassam S.
dc.contributor.authorUçan, Osman Nuri
dc.date.accessioned2021-05-15T12:50:04Z
dc.date.available2021-05-15T12:50:04Z
dc.date.issued2018
dc.departmentMühendislik ve Doğa Bilimleri Fakültesi, Elektrik - Elektronik Mühendisliği Bölümüen_US
dc.descriptionInternational Association of Researchers (IARES)
dc.description4th International Conference on Engineering and MIS, ICEMIS 2018 -- 19 June 2018 through 20 June 2018 -- -- 138526
dc.description.abstractFractal encoding promising proficiency in area of picture compressing but not used at compression of hyperspectral images. The paper presents a novel and applicable copy hyperspectral image lossy compressing founded in intra-prediction fractals bandwidth and hybrid between bands. The hyper spectral color picture is divided to different groups of bandings (GOB). So, the intraband estimate is used the first banding to each one GOB, overworking the spatial relation, as the form encrypting between banding through a resident exploration procedure is used to other bands at apiece (GOB), maximizing resident likeness among two together banding. The fractals constraints is contracted with coded Exponential-Golomb coding entropies. So, progress the decrypted value, the forecast mistake and the remaining fractal transform, quantize and encoded into entropy. Experimental compression results show that our scheme can achieve a actual high peak signal-to-noise ratio (PSNR) at low-slung bit degree and achieve a medium PSNR increase taking into account the overall bit complexity encoding rates compared to other lossless compression methods. Furthermore, the classification of the accuracy of our reconstructed image is 99.75%, which is better than the original uncompressed image. © Copyright 2018 ACM.en_US
dc.identifier.doi10.1145/3234698.3234705
dc.identifier.isbn9781450363921
dc.identifier.scopus2-s2.0-85052521735
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://doi.org/10.1145/3234698.3234705
dc.identifier.urihttps://hdl.handle.net/20.500.12939/1175
dc.identifier.wosWOS:000694697100007
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorAli, Bassam S.
dc.institutionauthorUçan, Osman Nuri
dc.language.isoen
dc.publisherAssociation for Computing Machineryen_US
dc.relation.ispartofACM International Conference Proceeding Series
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEstimateen_US
dc.subjectFractalsen_US
dc.subjectHyper Spectral Copyen_US
dc.subjectLossy Densityen_US
dc.titleLossy hyperspectral image compression based on intraband prediction and inter-band fractal
dc.typeConference Object

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Scopus İndeksli Yayınlar Koleksiyonu
Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu
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