scholarly journals Total variation vs L1 regularization: a comparison of compressive sensing optimization methods for chemical detection

2020 ◽  
Author(s):  
Elin Farnell ◽  
Henry Kvinge ◽  
Julia R. Dupuis ◽  
Michael J. Kirby ◽  
Chris Peterson ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Total Variation ◽  
Optimization Methods ◽  
Chemical Detection ◽  
L1 Regularization

Comparison of different lithographic source optimization methods based on compressive sensing

2020 ◽  
Author(s):  
Zhiqiang Wang ◽  
Xu Ma ◽  
Rui Chen ◽  
Gonzalo Arce ◽  
Lisong Dong ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Optimization Methods

Fast total-variation based image restoration based on derivative alternated direction optimization methods

2015 ◽  
Vol 170 ◽  
pp. 201-212 ◽  
Author(s):  
Dongwei Ren ◽  
Hongzhi Zhang ◽  
David Zhang ◽  
Wangmeng Zuo
Keyword(s):  
Image Restoration ◽  
Total Variation ◽  
Optimization Methods

scholarly journals Improved TV-CS Approaches for Inverse Scattering Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
M. T. Bevacqua ◽  
L. Di Donato
Keyword(s):  
Compressive Sensing ◽  
Total Variation ◽  
Inverse Scattering ◽  
Scattering Problem ◽  
Inverse Scattering Problem ◽  
Scattering Problems ◽  
Piecewise Constant ◽  
Numerical Examples ◽  
Inverse Scattering Problems

Total Variation and Compressive Sensing (TV-CS) techniques represent a very attractive approach to inverse scattering problems. In fact, if the unknown is piecewise constant and so has a sparse gradient, TV-CS approaches allow us to achieve optimal reconstructions, reducing considerably the number of measurements and enforcing the sparsity on the gradient of the sought unknowns. In this paper, we introduce two different techniques based on TV-CS that exploit in a different manner the concept of gradient in order to improve the solution of the inverse scattering problems obtained by TV-CS approach. Numerical examples are addressed to show the effectiveness of the method.

Improved total variation minimization method for compressive sensing by intra-prediction

2012 ◽  
Vol 92 (11) ◽  
pp. 2614-2623 ◽  
Author(s):  
Jie Xu ◽  
Jianwei Ma ◽  
Dongming Zhang ◽  
Yongdong Zhang ◽  
Shouxun Lin
Keyword(s):  
Compressive Sensing ◽  
Total Variation ◽  
Intra Prediction ◽  
Minimization Method ◽  
Total Variation Minimization
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