Adaptive total variation based image segmentation with semi-proximal alternating minimization

2021 ◽  
Vol 183 ◽  
pp. 108017
Author(s):  
Tingting Wu ◽  
Xiaoyu Gu ◽  
Youguo Wang ◽  
Tieyong Zeng
Keyword(s):  
Image Segmentation ◽  
Total Variation ◽  
Alternating Minimization ◽  
Adaptive Total Variation

scholarly journals Speckle Noise Removal by Energy Models with New Regularization Setting

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Bo Chen ◽  
Jinbin Zou ◽  
Weiqiang Zhang
Keyword(s):  
Total Variation ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Noise Removal ◽  
Energy Models ◽  
Energy Diffusion ◽  
Total Variation Model ◽  
Local Coordinates ◽  
Diffusion Speed ◽  
Adaptive Total Variation

In this paper, we introduce two novel total variation models to deal with speckle noise in ultrasound image in order to retain the fine details more effectively and to improve the speed of energy diffusion during the process. Firstly, two new convex functions are introduced as regularization term in the adaptive total variation model, and then, the diffusion performances of Hypersurface Total Variation (HYPTV) model and Logarithmic Total Variation (LOGTV) model are analyzed mathematically through the physical characteristics of local coordinates. We have shown that the larger positive parameter in the model is set, the greater energy diffusion speed appears to be, but it will cause the image to be too smooth that required adequate attention. Numerical experimental results show that our proposed LOGTV model for speckle noise removal is superior to traditional models, not only in visual effect but also in quantitative measures.

Adaptive total variation image deblurring: A majorization–minimization approach

2009 ◽  
Vol 89 (9) ◽  
pp. 1683-1693 ◽  
Author(s):  
João P. Oliveira ◽  
José M. Bioucas-Dias ◽  
Mário A.T. Figueiredo
Keyword(s):  
Total Variation ◽  
Image Deblurring ◽  
Adaptive Total Variation ◽  
Minimization Approach
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