DocumentCode :
809952
Title :
Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar
Author :
Varshney, Kush R. ; Cetin, Mujdat ; Fisher, John W., III ; Willsky, Alan S.
Author_Institution :
Lab. for Inf. & Decision Syst., Massachusetts Inst. of Technol., Cambridge, MA
Volume :
56
Issue :
8
fYear :
2008
Firstpage :
3548
Lastpage :
3561
Abstract :
Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structured, sparse signal representation algorithm for overcomplete dictionaries that can be decomposed into subdictionaries and whose dictionary elements can be arranged in a hierarchy. Around this algorithm, we construct a methodology for advanced image formation in wide-angle synthetic aperture radar (SAR), defining an approach for joint anisotropy characterization and image formation. Additionally, we develop a coordinate descent method for jointly optimizing a parameterized dictionary and recovering a sparse representation using that dictionary. The motivation is to characterize a phenomenon in wide-angle SAR that has not been given much attention before: migratory scattering centers, i.e., scatterers whose apparent spatial location depends on aspect angle. Finally, we address the topic of recovering solutions that are sparse in more than one objective domain by introducing a suitable sparsifying cost function. We encode geometric objectives into SAR image formation through sparsity in two domains, including the normal parameter space of the Hough transform.
Keywords :
image representation; radar imaging; synthetic aperture radar; SAR image formation; joint anisotropy characterization; sparse signal approximations; sparse signal representations; structured dictionaries; synthetic aperture radar application; Anisotropic magnetoresistance; Dictionaries; Inverse problems; Laboratories; Optimization methods; Radar scattering; Signal processing; Signal processing algorithms; Signal representations; Synthetic aperture radar; Hough transforms; inverse problems; optimization methods; overcomplete dictionaries; sparse signal representations; synthetic aperture radar; tree searching;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2008.919392
Filename :
4567680
Link To Document :
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