Joint Sparsity With Partially Known Support and Application to Ultrasound Imaging

We investigate the benefits of known partial support for the recovery of joint-sparse signals and demonstrate that it is advantageous in terms of recovery performance for both rank-blind and rank-aware algorithms. We suggest extensions of several joint-sparse recovery algorithms, e.g., simultaneous...

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Bibliographic Details
Published in:	IEEE signal processing letters Vol. 26; no. 1; pp. 84 - 88
Main Authors:	Besson, Adrien, Perdios, Dimitris, Wiaux, Yves, Thiran, Jean-Philippe
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Compressed sensing Greedy algorithms Image quality Image reconstruction Iterative algorithms Iterative methods joint sparsity Matching pursuit algorithms Multiple signal classification Multiplexing MUSIC Recovery Signal classification Signal processing algorithms Signal reconstruction Sparks Sparsity State of the art Subspace methods Ultrasonic imaging Ultrasonic testing Ultrasound
ISSN:	1070-9908, 1558-2361
Online Access:	Get full text
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