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Reducing spatially varying out-of-focus blur from natural image
Author(s) -
Faming Fang,
Fang Li,
Tieyong Zeng
Publication year - 2017
Publication title -
inverse problems and imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.755
H-Index - 40
eISSN - 1930-8345
pISSN - 1930-8337
DOI - 10.3934/ipi.2017004
Subject(s) - focus (optics) , computer science , kernel (algebra) , image (mathematics) , image restoration , frame (networking) , algorithm , artificial intelligence , computer vision , mathematical optimization , image processing , mathematics , optics , telecommunications , physics , combinatorics
In this paper, we focus on the challenging problem of removing the spatially varying out-of-focus blur from a single natural image. We first propose an effective method to estimate the blur map by the total variation refinement on Holder coefficient, then discuss the properties of the corresponding kernel matrix. A tight-frame based energy functional, whose minimizer is related to the optimal defocus result, is thus built. For tackling functional more efficiently, we describe the numerical procedure based on an accelerated primal-dual scheme. To verify the effectiveness of our method, we compare it with some state-of-the-art schemes using both synthesized and natural images. Experimental results demonstrate that the proposed method performs better than the compared methods.

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