Image Deblurring using Split Bregman Iterative Algorithm
Pages : 3518-3520
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Abstract
This paper presents a new variational algorithm for image deblurring by characterizing the properties of image local
smoothness and nonlocal self-similarity simultaneously. Specifically, the local smoothness is measured by a Total
Variation method, enforcing the local smoothness of images, while the nonlocal self similarity is measured by
transforming the 3D array generated by grouping similar image patches. A new Split Bregman-based algorithm is
developed to efficiently solve the above optimization problem. Extensive experiments on image deblurring verify the
effectiveness of the proposed algorithm.
Keywords: Image deblurring, local smoothness, nonlocal self-similarity
Article published in International Journal of Current Engineering and Technology, Vol.5, No.6 (Dec-2015)