Nonconvex Optimization with Alternating Direction Method of Multipliers for Tensor-Based Compressed Sensing with Group Sparsity

2017 ◽  
Author(s):  
Yong Li ◽  
Wenrui Dai ◽  
Hongkai Xiong
Keyword(s):  
Compressed Sensing ◽  
Nonconvex Optimization ◽  
Alternating Direction Method ◽  
Method Of Multipliers ◽  
Group Sparsity ◽  
Alternating Direction

scholarly journals Signal Reconstruction of Compressed Sensing Based on Alternating Direction Method of Multipliers

2019 ◽  
Vol 39 (1) ◽  
pp. 307-323 ◽  
Author(s):  
Yanliang Zhang ◽  
Xingwang Li ◽  
Guoying Zhao ◽  
Bing Lu ◽  
Charles C. Cavalcante
Keyword(s):  
Compressed Sensing ◽  
Signal Reconstruction ◽  
Alternating Direction Method ◽  
Method Of Multipliers ◽  
Alternating Direction

Image denoising algorithm of compressed sensing based on alternating direction method of multipliers

2021 ◽  
pp. 2250009
Author(s):  
Changjie Fang ◽  
Jingyu Chen ◽  
Shenglan Chen
Keyword(s):  
Compressed Sensing ◽  
Convergence Rate ◽  
Objective Function ◽  
Image Denoising ◽  
Alternating Direction Method ◽  
Method Of Multipliers ◽  
Alternating Direction ◽  
Time Simulation ◽  
Optimal Value ◽  
Simulation Results

In this paper, we propose an image denoising algorithm for compressed sensing based on alternating direction method of multipliers (ADMM). We prove that the objective function of the iterates approaches the optimal value. We also prove the [Formula: see text] convergence rate of our algorithm in the ergodic sense. At the same time, simulation results show that our algorithm is more efficient in image denoising compared with existing methods.

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