Abstract
This paper introduces a new low rank texture image denoising algorithm, which can restore low rank texture contaminated by both Gaussian and salt-and-pepper noise. The algorithm formulates texture image denoising in terms of solving a low rank matrix optimization problem. Simply assuming low rank is insufficient to describe the properties of natural images, causing high noise amplitudes which lead to unsatisfactory denoising results or serious loss of image details. Thus, in addition to the low rank assumption, the continuity of natural images is also assumed by the algorithm, by adding a total variation regularizer to the optimization objective function. We further give an effective algorithm to solve this optimization problem. By combining the low rank and continuity assumptions, the proposed algorithm overcomes the deficiencies of using either the low rank assumption or total variation regularization alone. Experiments show that our algorithm can effectively remove mixed noise in low rank texture images, and is better than existing algorithms in both its subjective visual effects and in terms of quantitative objective measures.
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Xiao Liang is currently a Ph.D. student in computer science and technology at the Institute for Advanced Study in Tsinghua University, Beijing, China. Her adviser is Prof. Harry Shum. She received her B.E. degree in electronic engineering from Tsinghua University. During her study, she interned at Microsoft Research Asia for over four years. Her research interests include texture processing, 3D computer vision and sparsity, and low rank matrix recovery.
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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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Liang, X. Removing mixed noise in low rank textures by convex optimization. Comp. Visual Media 2, 267–276 (2016). https://doi.org/10.1007/s41095-016-0056-2
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DOI: https://doi.org/10.1007/s41095-016-0056-2