scholarly journals A novel weighted total variation model for image denoising

2021 ◽  
Author(s):  
Meng‐Meng Li ◽  
Bing‐Zhao Li
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Total Variation Model ◽  
Weighted Total Variation ◽  
Variation Model

Image Denoising Based on Seperable Total Variation Model

2014 ◽  
Vol 43 (9) ◽  
pp. 910003
Author(s):  
胡辽林 HU Liao-lin ◽  
王斌 WANG Bin ◽  
薛瑞洋 XUE Rui-yang ◽  
王亚萍 WANG Ya-ping
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Total Variation Model ◽  
Variation Model

scholarly journals Image denoising via an improved non-local total variation model

2018 ◽  
Vol 2018 (8) ◽  
pp. 745-752 ◽  
Author(s):  
Yunjiao Bai ◽  
Yi Liu ◽  
Quan Zhang ◽  
Lina Jia ◽  
Zhiguo Gui
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Total Variation Model ◽  
Non Local ◽  
Variation Model

scholarly journals Local and Nonlocal Steering Kernel Weighted Total Variation Model for Image Denoising

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 329 ◽  
Author(s):  
Rui Lai ◽  
Yiguo Mo ◽  
Zesheng Liu ◽  
Juntao Guan
Keyword(s):  
Image Denoising ◽  
Total Variation ◽  
Noise Suppression ◽  
Nonlocal Symmetry ◽  
Visual Appearance ◽  
Quantitative Indices ◽  
Proposed Model ◽  
Total Variation Model ◽  
Weighted Total Variation ◽  
Tv Model

To eliminate heavy noise and retain more scene details, we propose a structure-oriented total variation (TV) model based on data dependent kernel function and TV criterion for image denoising application. The innovative model introduces the weights produced from the local and nonlocal symmetry features involved in the image itself to pick more precise solutions in the TV denoising process. As a result, the proposed local and nonlocal steering kernel weighted TV model yields excellent noise suppression and structure-preserving performance. The experimental results verify the validity of the proposed model in objective quantitative indices and subjective visual appearance.

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