@inproceedings{e5e5c3f4d30544fc919cbcd51afb10fd,
title = "L 0-norm and total variation for wavelet inpainting",
abstract = "In this paper, we suggest an algorithm to recover an image whose wavelet coefficients are partially lost. We propose a wavelet inpainting model by using L 0-norm and the total variation (TV) minimization. Traditionally, L 0-norm is replaced by L 1-norm or L 2-norm due to numerical difficulties. We use an alternating minimization technique to overcome these difficulties. In order to improve the numerical efficiency, we also apply a graph cut algorithm to solve the subproblem related to TV minimization. Numerical results will be given to demonstrate our advantages of the proposed algorithm.",
author = "Yau, {Andy C.} and Tai, {Xue Cheng} and Ng, {Michael K.}",
note = "Funding information: The research is supported by MOE (Ministry of Education) Tier II project T207N2202 and IDM project NRF2007IDMIDM002-010. In addition, the support from SUG 20/07 is also gratefully acknowledged. Publisher copyright: {\textcopyright} 2009 Springer-Verlag Berlin Heidelberg; 2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009 ; Conference date: 01-06-2009 Through 05-06-2009",
year = "2009",
month = jun,
doi = "10.1007/978-3-642-02256-2_45",
language = "English",
isbn = "3642022553",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), LNCS",
publisher = "Springer-Verlag Berlin Heidelberg",
pages = "539--551",
editor = "Tai, {Xue Cheng} and Knut M{\o}rken and Marius Lysaker and Lie, {Knut Andreas}",
booktitle = "Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings",
}