Title
A Novel Single-Step Approach for Self-Coherent Tomography Using Semidefinite Relaxation
Abstract
This letter presents a novel single-step approach for self-coherent tomography using semidefinite relaxation. Phase retrieval for scattered fields is not required. The general solver can be used to solve the corresponding convex optimization problem and image the target. Both man-made and experimental data is exploited to demonstrate the performance of the proposed approach. The imaging results illustrate the benefit of bringing the state-of-the-art mathematics to inverse scattering or diffraction tomography.
Year
DOI
Venue
2014
10.1109/LGRS.2013.2248117
IEEE Geosci. Remote Sensing Lett.
Keywords
Field
DocType
optical tomography,inverse scattering,diffraction tomography,phase retrieval,convex optimization problem,semidefinite relaxation,single-step approach,image retrieval,state-of-the-art mathematics,convex optimization,semidefinite programming (sdp),relaxation,self-coherent tomography,wireless tomography
Image retrieval,Artificial intelligence,Optical tomography,Inverse scattering problem,Computer vision,Mathematical optimization,Diffraction tomography,Phase retrieval,Algorithm,Tomography,Solver,Convex optimization,Mathematics
Journal
Volume
Issue
ISSN
11
1
1545-598X
Citations 
PageRank 
References 
3
0.48
6
Authors
4
Name
Order
Citations
PageRank
Zhen Hu115112.04
Robert Caiming Qiu285788.17
James P. Browning3212.47
Michael C. Wicks411914.06