Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/99124
標題: A regularization model with adaptive diffusivity for variational image denoising
作者: Po-Wen Hsieh
Pei-Chiang Shao
Suh-Yuh Yang
謝博文
關鍵字: Image denoising;Total variation;Regularization;Adaptivity;Split Bregman iteration
出版社: SIGNAL PROCESSING
Project: Signal Processing Volume 149, August 2018, Pages 214-228
摘要: 
In this paper, motivated by approximating the Euler-Lagrange equation of the pth-order regularization for 0 < p ≤ 1, we propose a new regularization model with adaptive diffusivity for variational image denoising. The model is equipped with a regularization controller which is introduced to adaptively adjust the diffusivity from pixel to pixel according to the magnitude of image gradient. The associated energy functional is convex and thus the minimization problem can be efficiently solved using a modified split Bregman iterative scheme. A convergence analysis of the iterative scheme is established. Numerical experiments are performed to demonstrate the good performance of the proposed model. Comparisons with some other image denoising models are also made.
URI: http://hdl.handle.net/11455/99124
DOI: 10.1016/j.sigpro.2017.12.011
Appears in Collections:應用數學系所

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