Image Super-Resolution via Wavelet Feature Extraction and Sparse Representation

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dc.contributor.authorAlvarez-Ramos, Valentin
dc.contributor.authorPonomaryov, Volodymyr
dc.contributor.authorSadovnychiy, Sergiy
dc.coverage.issue2cs
dc.coverage.volume27cs
dc.date.accessioned2018-06-18T12:49:20Z
dc.date.available2018-06-18T12:49:20Z
dc.date.issued2018-06cs
dc.description.abstractThis paper proposes a novel Super-Resolution (SR) technique based on wavelet feature extraction and sparse representation. First, the Low-Resolution (LR) image is interpolated employing the Lanczos operation. Then, the image is decomposed into sub-bands (LL, LH, HL and HH) via Discrete Wavelet Transform (DWT). Next, the LH, HL and HH sub-bands are interpolated employing the Lanczos interpolator. Principal Component Analysis (PCA) is used to reduce and to obtain the most relevant features information from the set of interpolated sub-bands. Overlapping patches are taken from the features obtained via PCA. For each patch, the sparse representation is computed using the Orthogonal Matching Pursuit (OMP) algorithm and the LR dictionary. Subsequently, this sparse representation is used to reconstruct a High-Resolution (HR) patch employing the HR dictionary and it is added to the LR image. By applying the quality objective criteria PSNR and SSIM, the novel technique has been evaluated demonstrating the superiority of the novel framework against state-of-the-art techniques.en
dc.formattextcs
dc.format.extent602-609cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2018 vol. 27, č. 2, s. 602-609. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2018.0602en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/83045
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2018/18_02_0602_0609.pdfcs
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSuper-resolutionen
dc.subjectsparse representationen
dc.subjectwaveleten
dc.subjectfeaturesen
dc.subjectinterpolationen
dc.subjectneural networksen
dc.titleImage Super-Resolution via Wavelet Feature Extraction and Sparse Representationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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