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Decomp2d: An R solution for image decomposition

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dc.contributor.authorOh, Hee-Seok-
dc.contributor.authorChoi, Guebin-
dc.contributor.authorKim, Donghoh-
dc.date.accessioned2022-10-12T00:35:35Z-
dc.date.available2022-10-12T00:35:35Z-
dc.date.created2022-08-25-
dc.date.created2022-08-25-
dc.date.created2022-08-25-
dc.date.created2022-08-25-
dc.date.created2022-08-25-
dc.date.created2022-08-25-
dc.date.issued2022-07-
dc.identifier.citationSoftwareX, Vol.19, p. 101182-
dc.identifier.issn2352-7110-
dc.identifier.urihttps://hdl.handle.net/10371/185851-
dc.description.abstractThe subjects of image processing include feature extraction, compression, denoising, image enhancement, and restoration. Many softwares have been developed for these studies. However, few studies have focused on decomposition in the literature, even though image decomposition is essential for image processing. This paper reviews several two-dimensional methods that can be adapted for image decomposition. Furthermore, we provide an R solution termed Decomp2d, tailored to the viewpoint of image decomposition based on existing R packages. © 2022 The Author(s)-
dc.language영어-
dc.publisherElsevier BV-
dc.titleDecomp2d: An R solution for image decomposition-
dc.typeArticle-
dc.identifier.doi10.1016/j.softx.2022.101182-
dc.citation.journaltitleSoftwareX-
dc.identifier.wosid000879382700012-
dc.identifier.scopusid2-s2.0-85135889954-
dc.citation.startpage101182-
dc.citation.volume19-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorOh, Hee-Seok-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusEMPIRICAL MODE DECOMPOSITION-
dc.subject.keywordPlusSINGULAR SPECTRUM ANALYSIS-
dc.subject.keywordPlusEMD-
dc.subject.keywordAuthorDecomposition-
dc.subject.keywordAuthorFrequency-
dc.subject.keywordAuthorImage-
dc.subject.keywordAuthorR package-
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