Title :
Synthetic aperture inversion with sparsity constraints
Author :
Yazici, Birsen ; Wang, Ling ; Duman, Kaan
Author_Institution :
Dept. of Electr., Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
In this paper, we introduced a novel approach to SAR image formation with sparsity constraints. We formulate the sparse SAR image reconstruction problem as an Lp-norm constrained quadratic inversion problem and approximate it with a sequence of L2-norm constrained problems. We addressed each of L2-norm constrained problem analytically using microlocal techniques. Our inversion method can be implemented efficiently at every iteration using the fast computation of Fourier Integral Operators.
Keywords :
Fourier transforms; image reconstruction; iterative methods; synthetic aperture radar; Fourier integral operators; SAR image formation; fast computation; iteration; microlocal techniques; quadratic inversion problem; sparse SAR image reconstruction problem; sparsity constraints; synthetic aperture inversion; Apertures; Image reconstruction; Imaging; Iterative methods; Noise; Radar imaging; Synthetic aperture radar;
Conference_Titel :
Electromagnetics in Advanced Applications (ICEAA), 2011 International Conference on
Conference_Location :
Torino
Print_ISBN :
978-1-61284-976-8
DOI :
10.1109/ICEAA.2011.6046285