Nonparametric optimization of constrained total variation for tomography reconstruction

2013 ◽  
Vol 43 (12) ◽  
pp. 2163-2176 ◽  
Author(s):  
Li Liu ◽  
Zhaofang Yin ◽  
Xueyun Ma
Keyword(s):  
Total Variation ◽  
Tomography Reconstruction

scholarly journals Deflection Tomography Reconstruction Based on Diagonal Total Variation

2018 ◽  
Vol 246 ◽  
pp. 03022
Author(s):  
Huaxin Li ◽  
Jinxiao Pan
Keyword(s):  
Sparse Representation ◽  
Total Variation ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
High Quality ◽  
Directional Information ◽  
Field Reconstruction ◽  
Tomography Reconstruction ◽  
Measured Field ◽  
Representation Method

In view of the shortages of the reconstruction algorithm based on Total Variation (TV) minimum under the framework of measured field compressed sensing, we study the measured field sparse representation method and solving method of optimization equation, and propose the measured field reconstruction algorithms based on Diagonal Total Variation (DTV). When there is no obvious change in the reconstruction iteration of TV, gradient transformation of diagonal direction is introduced, the multi-directional information is used to obtain a more sparse representation of the measured field in the reconstruction. Under the condition of sparse projections, experimental results of this algorithm are demonstrated and compared with the results from the TV method. Comparisons show that this method can reconstruct high-quality measured field.

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