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dc.contributor.authorPalomares Muñoz, José Manueles_ES
dc.contributor.authorPrieto, Albertoes_ES
dc.contributor.authorRos, Eduardoes_ES
dc.contributor.authorGonzález, Jesúses_ES
dc.date.accessioned2010-12-29T09:34:27Z
dc.date.available2010-12-29T09:34:27Z
dc.date.issued2006
dc.identifier.issn1057-7149
dc.identifier.urihttp://hdl.handle.net/10396/3956
dc.description.abstractThe logarithmic image processing model (LIP) is a robust mathematical framework, which, among other benefits, behaves invariantly to illumination changes. This paper presents, for the first time, two general formulations of the 2-D convolution of separable kernels under the LIP paradigm. Although both formulations are mathematically equivalent, one of them has been designed avoiding the operations which are computationally expensive in current computers. Therefore, this fast LIP convolution method allows to obtain significant speedups and is more adequate for real-time processing. In order to support these statements, some experimental results are shown in Section V.en
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoengen
dc.publisherIEEEes_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.sourceIeee Transactions on Image Processing 15 (11), 3602-3608 (2006)es_ES
dc.subjectConvolutionen
dc.subjectLogarithmic Image Processing (Lip) Averageen
dc.subjectLip Sobel Edge-Detectionen
dc.subjectLip Gaussian Bluren
dc.titleGeneral logarithmic image processing convolutionen
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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