Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.acha.2011.06.001
Title: Wavelet frame based blind image inpainting
Authors: Dong, B.
Ji, H. 
Li, J.
Shen, Z. 
Xu, Y. 
Keywords: Image inpainting
Sparse approximation
Split Bregman algorithm
Wavelet frame
Issue Date: Mar-2012
Citation: Dong, B., Ji, H., Li, J., Shen, Z., Xu, Y. (2012-03). Wavelet frame based blind image inpainting. Applied and Computational Harmonic Analysis 32 (2) : 268-279. ScholarBank@NUS Repository. https://doi.org/10.1016/j.acha.2011.06.001
Abstract: Image inpainting has been widely used in practice to repair damaged/missing pixels of given images. Most of the existing inpainting techniques require knowing beforehand where those damaged pixels are, either given as a priori or detected by some pre-processing. However, in certain applications, such information neither is available nor can be reliably pre-detected, e.g. removing random-valued impulse noise from images or removing certain scratches from archived photographs. This paper introduces a blind inpainting model to solve this type of problems, i.e., a model of simultaneously identifying and recovering damaged pixels of the given image. A tight frame based regularization approach is developed in this paper for such blind inpainting problems, and the resulted minimization problem is solved by the split Bregman algorithm first proposed by Goldstein and Osher (2009) [1]. The proposed blind inpainting method is applied to various challenging image restoration tasks, including recovering images that are blurry and damaged by scratches and removing image noise mixed with both Gaussian and random-valued impulse noise. The experiments show that our method is compared favorably against many available two-staged methods in these applications. © 2011 Published by Elsevier Inc.
Source Title: Applied and Computational Harmonic Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/115356
ISSN: 10635203
DOI: 10.1016/j.acha.2011.06.001
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