A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising

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The code in this package implements the Trilateral Weighted Sparse Coding Scheme for real color image denoising as described in the following paper ” A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising”.

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Authors J. Xu, L. Zhang, D. Zhang
Journal/Conference Name Computer Vision - ECCV 2018: 15th European Conference, Munich, Germany
Paper Category
Paper Abstract Most of existing image denoising methods assume the corrupted noise to be additive white Gaussian noise (AWGN). However,the realistic noise in real-world noisy images is much more complex than AWGN, and is hard to be modeled by simple analytical distributions. As a result, many state-of-the-art denoising methods in literature become much less effective when applied to real-world noisy images captured by CCD or CMOS cameras. In this paper, we develop a trilateral weighted sparse coding (TWSC) scheme for robust real-world image denoising. Specifically, we introduce three weight matrices into the data and regularization terms of the sparse coding framework to characterize the statistics of realistic noise and image priors. TWSC can be reformulated as a linear equality-constrained problem and can be solved by the alternating direction method of multipliers. The existence and uniqueness of the solution and convergence of the proposed algorithm are analyzed. Extensive experiments demonstrate that the proposed TWSC scheme outperforms state-of-the-art denoising methods on removing realistic noise.
Date of publication 2018
Code Programming Language MATLAB

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