A Noise-Suppressing and Edge-Preserving Multiframe Super-Resolution Image Reconstruction Method

dc.creatorMaiseli, Baraka J.
dc.creatorAlly, Nassor
dc.creatorGao, Huijun
dc.date2016-09-09T09:49:37Z
dc.date2016-09-09T09:49:37Z
dc.date2015
dc.date.accessioned2018-03-27T08:53:01Z
dc.date.available2018-03-27T08:53:01Z
dc.descriptionSuper-resolution technology is an approach that helps to restore high quality images and videos from degraded ones. The method stems from an ill-posed minimization problem, which is usually solved using the L2 norm and some regularization techniques. Most of the classical regularizing functionals are based on the Total Variation and the Perona–Malik frameworks, which suffer from undesirable artifacts (blocking and staircasing). To address these problems, we have developed a super-resolution framework that integrates an adaptive diffusion-based regularizer. The model is feature-dependent: linear isotropic in flat regions, a condition that regularizes an image uniformly and removes noise more effectively; and nonlinear anisotropic near boundaries, which helps to preserve important image features, such as edges and contours. Additionally, the new regularizing kernel incorporates a shape-defining parameter that can be automatically updated to ensure convexity and stability of the corresponding energy functional. Comparisons with other methods show that our method is superior and, more importantly, can achieve higher reconstruction factors.
dc.identifierMaiseli, B.J., Ally, N. and Gao, H., 2015. A noise-suppressing and edge-preserving multiframe super-resolution image reconstruction method. Signal Processing: Image Communication, 34, pp.1-13.
dc.identifierhttp://hdl.handle.net/20.500.11810/3690
dc.identifier10.1016/j.image.2015.03.001
dc.identifier.urihttp://hdl.handle.net/20.500.11810/3690
dc.languageen
dc.publisherElsevier
dc.subjectConvex optimization
dc.subjectSuper-resolution
dc.subjectBackward diffusion
dc.subjectRegularization
dc.titleA Noise-Suppressing and Edge-Preserving Multiframe Super-Resolution Image Reconstruction Method
dc.typeJournal Article, Peer Reviewed

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