New time dependent pretreat models based on total variational image restoration |
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Authors: | Jing Xu Qian-shun Chang |
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Institution: | Jing Xu 1,2,Qian-shun Chang 3 1 School of Statistics and Mathematics,Zhejiang Gongshang University,Hangzhou 310018,China 2 Division of Mathematical Sciences,School of Physical and Mathematical Sciences,Nanyang Technological University,50 Nanyang Avenue,Singapore 639798 3 Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 110190,China |
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Abstract: | In this paper, we propose new pretreat models for total variation (TV) minimization problems in image deblurring and denoising.
Specially, blur operator is considered as useful information in restoration. New models in form is equivalent to pretreat
the initial value by image blur operator. We successfully get a new (L. Rudin, S. Osher, and E. Fatemi) ROF model, a new level
set motion model and a new anisotropic diffusion model respectively. Numerical experiments demonstrate that, under the same
stopping rule, the proposed methods significantly accelerate the convergence of the mothed, save computation time and get
the same restored effect. |
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Keywords: | Total variation image restoration level set motion anisotropic diffusion PSNR |
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