A fast minimization method for blur and multiplicative noise removal

2013 ◽  
Vol 90 (1) ◽  
pp. 48-61 ◽  
Author(s):  
Fan Wang ◽  
Michael K. Ng
Keyword(s):  
Multiplicative Noise ◽  
Noise Removal ◽  
Minimization Method ◽  
Multiplicative Noise Removal

scholarly journals A hybrid regularizers model for multiplicative noise removal

2021 ◽  
pp. 40-50
Author(s):  
Thi Thu Thao Tran ◽  
Cong Thang Pham ◽  
Duc Hong Vo ◽  
Duc Hoang Vo
Keyword(s):  
Variational Method ◽  
Minimization Problem ◽  
Existence And Uniqueness ◽  
Multiplicative Noise ◽  
State Of The Art ◽  
Noise Removal ◽  
Alternating Minimization ◽  
Minimization Method ◽  
Multiplicative Noise Removal ◽  
Alternating Minimization Method

In this paper, we propose a variational method for restoring images corrupted by multiplicative noise. Computationally, we employ the alternating minimization method to solve our minimization problem. We also study the existence and uniqueness of the proposed problem. Finally, experimental results are provided to demonstrate the superiority of our proposed hybrid model and algorithm for image denoising in comparison with state-of-the-art methods.

scholarly journals A Fast High-Order Total Variation Minimization Method for Multiplicative Noise Removal

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Xiao-Guang Lv ◽  
Jiang Le ◽  
Jin Huang ◽  
Liu Jun
Keyword(s):  
Total Variation ◽  
Multiplicative Noise ◽  
Noise Removal ◽  
High Order ◽  
Alternating Minimization ◽  
Minimization Method ◽  
Total Variation Minimization ◽  
Alternating Minimization Algorithm ◽  
Staircase Effect ◽  
Multiplicative Noise Removal

Multiplicative noise removal problem has received considerable attention in recent years. The total variation regularization method for the solution of the noise removal problem can preserve edges well but has the sometimes undesirable staircase effect. In this paper, we propose a fast high-order total variation minimization method to restore multiplicative noisy images. The proposed method is able to preserve edges and at the same time avoid the staircase effect in the smooth regions. An alternating minimization algorithm is employed to solve the proposed high-order total variation minimization problem. We discuss the convergence of the alternating minimization algorithm. Some numerical results show that the proposed method gives restored images of higher quality than some existing multiplicative noise removal methods.

Iteratively Reweighted Anisotropic-TV Based Multiplicative Noise Removal Model

2012 ◽  
Vol 38 (3) ◽  
pp. 444-451 ◽  
Author(s):  
Xu-Dong WANG ◽  
Xiang-Chu FENG ◽  
Lei-Gang HUO
Keyword(s):  
Multiplicative Noise ◽  
Noise Removal ◽  
Multiplicative Noise Removal ◽  
Removal Model
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