IEEE Trans Image Process - Super resolution image reconstruction through Bregman iteration using morphologic regularization.

Tópicos

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Resumo

Multiscale morphological operators are studied extensively in the literature for image processing and feature extraction purposes. In this paper, we model a nonlinear regularization method based on multiscale morphology for edge-preserving super resolution (SR) image reconstruction. We formulate SR image reconstruction as a deblurring problem and then solve the inverse problem using Bregman iterations. The proposed algorithm can suppress inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently. Experimental results show the effectiveness of the proposed regularization and reconstruction method for SR image.

Resumo Limpo

multiscal morpholog oper studi extens literatur imag process featur extract purpos paper model nonlinear regular method base multiscal morpholog edgepreserv super resolut sr imag reconstruct formul sr imag reconstruct deblur problem solv invers problem use bregman iter propos algorithm can suppress inher nois generat lowresolut imag format well sr imag estim effici experiment result show effect propos regular reconstruct method sr imag

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