Please use this identifier to cite or link to this item: https://doi.org/10.1109/TIP.2009.2019806
Title: A fast optimization transfer algorithm for image inpainting in wavelet domains
Authors: Chan, R.H.
Wen, Y.-W. 
Yip, A.M. 
Keywords: Alternating minimization
Image inpainting
Optimization transfer
Total variation
Wavelet
Issue Date: 2009
Source: Chan, R.H., Wen, Y.-W., Yip, A.M. (2009). A fast optimization transfer algorithm for image inpainting in wavelet domains. IEEE Transactions on Image Processing 18 (7) : 1467-1476. ScholarBank@NUS Repository. https://doi.org/10.1109/TIP.2009.2019806
Abstract: A wavelet inpainting problem refers to the problem of filling in missing wavelet coefficients in an image. A variational approach was used by Chan et al. The resulting functional was minimized by the gradient descent method. In this paper, we use an optimization transfer technique which involves replacing their univariate functional by a bivariate functional by adding an auxiliary variable. Our bivariate functional can be minimized easily by alternating minimization: for the auxiliary variable, the minimum has a closed form solution, and for the original variable, the minimization problem can be formulated as a classical total variation (TV) denoising problem and, hence, can be solved efficiently using a dual formulation. We show that our bivariate functional is equivalent to the original univariate functional. We also show that our alternating minimization is convergent. Numerical results show that the proposed algorithm is very efficient and outperforms that of Chan et al. © 2009 IEEE.
Source Title: IEEE Transactions on Image Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/52749
ISSN: 10577149
DOI: 10.1109/TIP.2009.2019806
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