Image and Signal Processing Methods

Comparison of efficient sparse reconstruction techniques applied to inverse synthetic aperture radar images

[+] Author Affiliations
Luca Pasca, Niccolò Ricardi, Pietro Savazzi, Fabio Dell’Acqua, Paolo Gamba

University of Pavia, Department of Electrical, Computer, Biomedical Engineering, via Adolfo Ferrata, 5, I-27100 Pavia, Italy

J. Appl. Remote Sens. 9(1), 095071 (Jul 07, 2015). doi:10.1117/1.JRS.9.095071
History: Received February 3, 2015; Accepted June 9, 2015
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Abstract.  Compressed sensing can be a valuable method with which to acquire high-resolution images, reducing the stored amount of information. This objective may be pursued without using any prior knowledge of the images, unlike the standard information compression algorithms do. Information compression can be obtained by a simple matrix multiplication, but the process of reconstructing the original image could be very expensive in terms of computation requirements. We are interested in comparing different reconstruction techniques for compressed air-to-air inverse synthetic aperture radar images, looking for a sensible compromise between performance results and complexity. In more detail, the compared algorithms are iterative thresholding, basis pursuit and convex optimization. Furthermore, particular attention has been devoted to a more appropriate way of splitting large-sized images in order to obtain smaller matrices with uniform sparseness for reducing the computational load.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Luca Pasca ; Niccolò Ricardi ; Pietro Savazzi ; Fabio Dell’Acqua and Paolo Gamba
"Comparison of efficient sparse reconstruction techniques applied to inverse synthetic aperture radar images", J. Appl. Remote Sens. 9(1), 095071 (Jul 07, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095071


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