Computational enhancement of large scale environmental imagery: aggregation of robust numerical regularization, neural computing and digital dynamic filtering

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dc.contributor.authorShkvarko, Yuriy
dc.contributor.authorVillalón-Turrubiates, Iván E.
dc.date.accessioned2016-04-04T21:15:06Z
dc.date.available2016-04-04T21:15:06Z
dc.date.issued2007
dc.descriptionWe address a new efficient robust optimisation approach to large-scale environmental image reconstruction/enhancement as required for remote sensing imaging with multi-spectral array sensors/SAR. First, the problem-oriented robustification of the previously proposed Fused Bayesian-Regularization (FBR) enhanced imaging method is performed to alleviate its ill-poseness due to system-level and model-model uncertainties. Second, the modification of the Hopfield-type Maximum Entropy Neural Network (MENN) is proposed that enables such MENN to perform numerically the robustified FBR technique via computationally efficient iterative scheme. The efficiency of the aggregated robust regularised MENN technique is verified through simulation studies of enhancement of the real-world environmental images.es
dc.description.sponsorshipCINVESTAVes
dc.identifier.citationY. Shkvarko & I.E. Villalón-Turrubiates (2007). “Computational enhancement of large scale environmental imagery: aggregation of robust numerical regularization, neural computing and digital dynamic filtering”, International Journal of Computational Science and Engineering (IJCSE), 3(3), pp.219-231.es
dc.identifier.issn1742-7185
dc.identifier.urihttp://hdl.handle.net/11117/3235
dc.language.isoenges
dc.publisherInternational Journal of Computational Science and Engineering (IJCSE)es
dc.relation.ispartofseriesIJCSE;3(3)
dc.rights.urihttp://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdfes
dc.subjectNonlinear Regularisationes
dc.subjectImage Enhancementes
dc.subjectNumerical Inverse Problemses
dc.subjectEntropyes
dc.subjectNeural Networkses
dc.titleComputational enhancement of large scale environmental imagery: aggregation of robust numerical regularization, neural computing and digital dynamic filteringes
dc.typeinfo:eu-repo/semantics/articlees
rei.peerreviewedYeses
rei.revisorIJCSE

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