Image enhancement based on edge boosting algorithm

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dc.contributor.authorNgernplubpla, Jaturon
dc.contributor.authorChitsobhuk, Orachat
dc.date.accessioned2026-08-06T10:10:17Z
dc.date.available2026-08-06T10:10:17Z
dc.date.issued2015-01-01
dc.description.abstractIn this paper, a technique for image enhancement based on proposed edge boosting algorithm to reconstruct high quality image from a single low resolution image is described. The difficulty in single-image super-resolution is that the generic image priors resided in the low resolution input image may not be sufficient to generate the effective solutions. In order to achieve a success in super-resolution reconstruction, efficient prior knowledge should be estimated. The statistics of gradient priors in terms of priority map based on separable gradient estimation, maximum likelihood edge estimation, and local variance are introduced. The proposed edge boosting algorithm takes advantages of these gradient statistics to select the appropriate enhancement weights. The larger weights are applied to the higher frequency details while the low frequency details are smoothed. From the experimental results, the significant performance improvement quantitatively and perceptually is illustrated. It can be seen that the proposed edge boosting algorithm demonstrates high quality results with fewer artifacts, sharper edges, superior texture areas, and finer detail with low noise.
dc.identifier.citationProceedings of SPIE the International Society for Optical Engineering, 9817, 2015
dc.identifier.doi10.1117/12.2228234
dc.identifier.issn0277786X
dc.identifier.other2-s2.0-85028337825
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/5902
dc.sourceProceedings of SPIE the International Society for Optical Engineering
dc.subjectGradient based priors
dc.subjectImage enhancement
dc.subjectInverts filter
dc.subjectSuper resolution
dc.titleImage enhancement based on edge boosting algorithm
dc.typeConference Paper

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