Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method

Conventional compressive sensing (CS)-based imaging methods allow images to be reconstructed from a small amount of data, while they suffer from high computational burden even for a moderate scene. To address this problem, this paper presents a novel two-dimensional (2D) CS imaging algorithm for str...

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Autores principales:	Fangfang Shen, Xuyang Chen, Yanming Liu, Yaocong Xie, Xiaoping Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	synthetic aperture radar compressive sensing sparsity TV split bregman Science Q
Acceso en línea:	https://doaj.org/article/638827ba8e314c049e9c4c2841bc6b19
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spelling	oai:doaj.org-article:638827ba8e314c049e9c4c2841bc6b192021-11-11T18:50:44ZStrip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method10.3390/rs132142312072-4292https://doaj.org/article/638827ba8e314c049e9c4c2841bc6b192021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4231https://doaj.org/toc/2072-4292Conventional compressive sensing (CS)-based imaging methods allow images to be reconstructed from a small amount of data, while they suffer from high computational burden even for a moderate scene. To address this problem, this paper presents a novel two-dimensional (2D) CS imaging algorithm for strip-map synthetic aperture radars (SARs) with zero squint angle. By introducing a 2D separable formulation to model the physical procedure of the SAR imaging, we separate the large measurement matrix into two small ones, and then the induced algorithm can deal with 2D signal directly instead of converting it into 1D vector. As a result, the computational load can be reduced significantly. Furthermore, thanks to its superior performance in maintaining contour information, the gradient space of the SAR image is exploited and the total variation (TV) constraint is incorporated to improve resolution performance. Due to the non-differentiable property of the TV regularizer, it is difficult to directly solve the induced TV regularization problem. To overcome this problem, an improved split Bregman method is presented by formulating the TV minimization problem into a sequence of unconstrained optimization problem and Bregman updates. It yields an accurate and simple solution. Finally, the synthesis and real experiment results demonstrate that the proposed algorithm remains competitive in terms of high resolution and high computational efficiency.Fangfang ShenXuyang ChenYanming LiuYaocong XieXiaoping LiMDPI AGarticlesynthetic aperture radarcompressive sensingsparsityTVsplit bregmanScienceQENRemote Sensing, Vol 13, Iss 4231, p 4231 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	synthetic aperture radar compressive sensing sparsity TV split bregman Science Q
spellingShingle	synthetic aperture radar compressive sensing sparsity TV split bregman Science Q Fangfang Shen Xuyang Chen Yanming Liu Yaocong Xie Xiaoping Li Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
description	Conventional compressive sensing (CS)-based imaging methods allow images to be reconstructed from a small amount of data, while they suffer from high computational burden even for a moderate scene. To address this problem, this paper presents a novel two-dimensional (2D) CS imaging algorithm for strip-map synthetic aperture radars (SARs) with zero squint angle. By introducing a 2D separable formulation to model the physical procedure of the SAR imaging, we separate the large measurement matrix into two small ones, and then the induced algorithm can deal with 2D signal directly instead of converting it into 1D vector. As a result, the computational load can be reduced significantly. Furthermore, thanks to its superior performance in maintaining contour information, the gradient space of the SAR image is exploited and the total variation (TV) constraint is incorporated to improve resolution performance. Due to the non-differentiable property of the TV regularizer, it is difficult to directly solve the induced TV regularization problem. To overcome this problem, an improved split Bregman method is presented by formulating the TV minimization problem into a sequence of unconstrained optimization problem and Bregman updates. It yields an accurate and simple solution. Finally, the synthesis and real experiment results demonstrate that the proposed algorithm remains competitive in terms of high resolution and high computational efficiency.
format	article
author	Fangfang Shen Xuyang Chen Yanming Liu Yaocong Xie Xiaoping Li
author_facet	Fangfang Shen Xuyang Chen Yanming Liu Yaocong Xie Xiaoping Li
author_sort	Fangfang Shen
title	Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
title_short	Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
title_full	Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
title_fullStr	Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
title_full_unstemmed	Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method
title_sort	strip-map sar image formulation based on the modified alternating split bregman method
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/638827ba8e314c049e9c4c2841bc6b19
work_keys_str_mv	AT fangfangshen stripmapsarimageformulationbasedonthemodifiedalternatingsplitbregmanmethod AT xuyangchen stripmapsarimageformulationbasedonthemodifiedalternatingsplitbregmanmethod AT yanmingliu stripmapsarimageformulationbasedonthemodifiedalternatingsplitbregmanmethod AT yaocongxie stripmapsarimageformulationbasedonthemodifiedalternatingsplitbregmanmethod AT xiaopingli stripmapsarimageformulationbasedonthemodifiedalternatingsplitbregmanmethod
_version_	1718431704804229120

Strip-Map SAR Image Formulation Based on the Modified Alternating Split Bregman Method

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