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Compressive Sensing as Applied to Inverse Problems for Imaging: Theory, applications, current trends, and open challenges.

Abstract : Compressive sensing (CS) is currently one the most active research fields in information engineering and science. The flexibility, robustness, accuracy, effectiveness, and sound theory behind such a paradigm have motivated a great interest in developing and applying CS to many domains, including inverse scattering. Unfortunately, electromagnetic imaging problems have some unique theoretical features that prevent a straightforward exploitation of CS tools. Therefore, suitable CS-based strategies must be considered in such a framework.
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https://hal.archives-ouvertes.fr/hal-01656851
Contributor : Andrea Massa <>
Submitted on : Wednesday, December 6, 2017 - 10:19:38 AM
Last modification on : Wednesday, April 8, 2020 - 3:57:52 PM

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Giacomo Oliveri, Marco Salucci, Nicola Anselmi, Andrea Massa. Compressive Sensing as Applied to Inverse Problems for Imaging: Theory, applications, current trends, and open challenges.. IEEE Antennas and Propagation Magazine, Institute of Electrical and Electronics Engineers, 2017, IEEE Antennas and Propagation Magazine, 59 (5), pp.34 - 46. ⟨10.1109/MAP.2017.2731204⟩. ⟨hal-01656851⟩

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