Para citar este documento: http://ddd.uab.cat/record/86365
Combining Total Variation and Nonlocal Means Regularization for Edge Preserving Image Deconvolution
Hao, Binbin (China University of Petroleum)
Zhu, Jianguang (Shandong University of Science and Technology)

Fecha: 2011
Resumen: We propose a new edge preserving image deconvolution model by combining total variation and nonlocal means regularization. Natural images exhibit an high degree of redundancy. Using this redundancy, the nonlocal means regularization strategy is a good technique for detail preserving image restoration. In order to further improve the visual quality of the nonlocal means based algorithm, total variation is introduced to the model to better preserve edges. Then an efficient alternating minimization procedure is used to solve the model. Numerical experiments illustrate the effectiveness of the proposed algorithm.
Derechos: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Lengua: Anglès
Documento: article ; recerca ; publishedVersion
Materia: Total Variation Regularization ; Nonlocal Means Filter ; Image Deconvolution
Publicado en: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 10, Núm. 1 (December 2011) , p. 42-53, ISSN 1577-5097



11 p, 760.9 KB

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