Sparsity based regularization for microwave imaging with NESTA algorithm

Emre Yalcin; Ozgur Ozdemir; Ulas Taskin

doi:10.1109/CAMA.2017.8273426

Sparsity based regularization for microwave imaging with NESTA algorithm

Emre Yalcin, Ozgur Ozdemir, Ulas Taskin

Department of Electronics and Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

We propose a sparsity based regularization method, Born Iterative Method(BIM)-NESTA to enhance the resolution in sparse microwave imaging problems. The inverse problem is handled with conjunction of Born Iterative Method and NESTA algorithm by minimization of the cost function which consists measurement-data misfit and first-norm penalty term. Numerical results verify that BIM-NESTA method manages to reconstruct closely located object and possess edge preserving capability for sparse domain where traditional BIM with Tikhonov regularization fails.

Original language	English
Title of host publication	2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	282-283
Number of pages	2
ISBN (Electronic)	9781509050284
DOIs	https://doi.org/10.1109/CAMA.2017.8273426
Publication status	Published - 2 Jul 2017
Event	2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017 - Tsukuba, Japan Duration: 4 Dec 2017 → 6 Dec 2017

Publication series

Name	2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017
Volume	2018-January

Conference

Conference	2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017
Country/Territory	Japan
City	Tsukuba
Period	4/12/17 → 6/12/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

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10.1109/CAMA.2017.8273426

Cite this

Yalcin, E., Ozdemir, O., & Taskin, U. (2017). Sparsity based regularization for microwave imaging with NESTA algorithm. In 2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017 (pp. 282-283). (2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAMA.2017.8273426

@inproceedings{edd816d563fa4f1a890f2958acc6396c,

title = "Sparsity based regularization for microwave imaging with NESTA algorithm",

abstract = "We propose a sparsity based regularization method, Born Iterative Method(BIM)-NESTA to enhance the resolution in sparse microwave imaging problems. The inverse problem is handled with conjunction of Born Iterative Method and NESTA algorithm by minimization of the cost function which consists measurement-data misfit and first-norm penalty term. Numerical results verify that BIM-NESTA method manages to reconstruct closely located object and possess edge preserving capability for sparse domain where traditional BIM with Tikhonov regularization fails.",

author = "Emre Yalcin and Ozgur Ozdemir and Ulas Taskin",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017 ; Conference date: 04-12-2017 Through 06-12-2017",

year = "2017",

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doi = "10.1109/CAMA.2017.8273426",

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Yalcin, E, Ozdemir, O & Taskin, U 2017, Sparsity based regularization for microwave imaging with NESTA algorithm. in 2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017. 2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 282-283, 2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017, Tsukuba, Japan, 4/12/17. https://doi.org/10.1109/CAMA.2017.8273426

Sparsity based regularization for microwave imaging with NESTA algorithm. / Yalcin, Emre; Ozdemir, Ozgur; Taskin, Ulas.
2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 282-283 (2017 IEEE Conference on Antenna Measurements and Applications, CAMA 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ozdemir, Ozgur

AU - Taskin, Ulas

PY - 2017/7/2

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N2 - We propose a sparsity based regularization method, Born Iterative Method(BIM)-NESTA to enhance the resolution in sparse microwave imaging problems. The inverse problem is handled with conjunction of Born Iterative Method and NESTA algorithm by minimization of the cost function which consists measurement-data misfit and first-norm penalty term. Numerical results verify that BIM-NESTA method manages to reconstruct closely located object and possess edge preserving capability for sparse domain where traditional BIM with Tikhonov regularization fails.

AB - We propose a sparsity based regularization method, Born Iterative Method(BIM)-NESTA to enhance the resolution in sparse microwave imaging problems. The inverse problem is handled with conjunction of Born Iterative Method and NESTA algorithm by minimization of the cost function which consists measurement-data misfit and first-norm penalty term. Numerical results verify that BIM-NESTA method manages to reconstruct closely located object and possess edge preserving capability for sparse domain where traditional BIM with Tikhonov regularization fails.

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Sparsity based regularization for microwave imaging with NESTA algorithm

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