L1 regularization recovered SAR images based interferometric SAR imaging via complex approximated message passing

2017 ◽  
Author(s):  
Chenyang Wu ◽  
Hui Bi ◽  
Bingchen Zhang ◽  
Yun Lin ◽  
Wen Hong
Keyword(s):  
Message Passing ◽  
Sar Images ◽  
L1 Regularization ◽  
Sar Imaging ◽  
Interferometric Sar

scholarly journals Synthetic Aperture Radar Processing Approach for Simultaneous Target Detection and Image Formation

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3377 ◽  
Author(s):  
Jifang Pei ◽  
Yulin Huang ◽  
Weibo Huo ◽  
Yuxuan Miao ◽  
Yin Zhang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Target Detection ◽  
Time Domain ◽  
Image Formation ◽  
Visual Saliency ◽  
Synthetic Aperture ◽  
Sar Images ◽  
Saliency Maps ◽  
Sar Imaging ◽  
Sar Imagery

Finding out interested targets from synthetic aperture radar (SAR) imagery is an attractive but challenging problem in SAR application. Traditional target detection is independent on SAR imaging process, which is purposeless and unnecessary. Hence, a new SAR processing approach for simultaneous target detection and image formation is proposed in this paper. This approach is based on SAR imagery formation in time domain and human visual saliency detection. First, a series of sub-aperture SAR images with resolutions from low to high are generated by the time domain SAR imaging method. Then, those multiresolution SAR images are detected by the visual saliency processing, and the corresponding intermediate saliency maps are obtained. The saliency maps are accumulated until the result with a sufficient confidence level. After some screening operations, the target regions on the imaging scene are located, and only these regions are focused with full aperture integration. Finally, we can get the SAR imagery with high-resolution detected target regions but low-resolution clutter background. Experimental results have shown the superiority of the proposed approach for simultaneous target detection and image formation.

scholarly journals Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2336 ◽  
Author(s):  
Takashi Nonaka ◽  
Tomohito Asaka ◽  
Keishi Iwashita
Keyword(s):  
Phase Noise ◽  
Atmospheric Effects ◽  
Sar Images ◽  
Single Pass ◽  
Digital Elevation ◽  
Total Phase ◽  
Disaster Monitoring ◽  
The Difference ◽  
Elevation Model ◽  
Interferometric Sar

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.

scholarly journals COHERENT CHANGE DETECTION FOR REPEATED-PASS INTERFEROMETRIC SAR IMAGES: AN APPLICATION TO EARTHQUAKE DAMAGE ASSESSMENT ON BUILDINGS

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 383-388 ◽  
Author(s):  
D. Oxoli ◽  
P. Boccardo ◽  
M. A. Brovelli ◽  
M. E. Molinari ◽  
A. Monti Guarnieri
Keyword(s):  
Change Detection ◽  
Emergency Management ◽  
Performance Assessment ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Detection Sensitivity ◽  
Management Service ◽  
Sar Images ◽  
Coherent Change Detection ◽  
Interferometric Sar

<p><strong>Abstract.</strong> During disaster response, the availability of relevant information, delivered in a proper format enabling its use among the different actors involved in response efforts, is key to lessen the impact of the disaster itself. Focusing on the contribution of geospatial information, meaningful advances have been achieved through the adoption of satellite earth observations within emergency management practices. Among these technologies, the Synthetic Aperture Radar (SAR) imaging has been extensively employed for large-scale applications such as flood areas delineation and terrain deformation analysis after earthquakes. However, the emerging availability of higher spatial and temporal resolution data has uncovered the potential contribution of SAR to applications at a finer scale. This paper proposes an approach to enable pixel-wise earthquake damage assessments based on Coherent Change Detection methods applied to a stack of repeated-pass interferometric SAR images. A preliminary performance assessment of the procedure is provided by processing Sentinel-1 data stack related to the 2016 central Italy earthquake for the towns of Ametrine and Accumoli. Damage assessment maps from photo-interpretation of high-resolution airborne imagery, produced in the framework of Copernicus EMS (Emergency Management Service &amp;ndash; European Commission) and cross-checked with field survey, is used as ground truth for the performance assessment. Results show the ability of the proposed approach to automatically identify changes at an almost individual building level, thus enabling the possibility to empower traditional damage assessment procedures from optical imagery with the centimetric change detection sensitivity characterizing SAR. The possibility of disseminating outputs in a GIS-like format represents an asset for an effective and cross-cutting information sharing among decision makers and analysts.</p>

Unsupervised segmentation of multitemporal interferometric SAR images

1999 ◽  
Vol 37 (5) ◽  
pp. 2259-2271 ◽  
Author(s):  
P.B.G. Dammert ◽  
J.I.H. Askne ◽  
S. Kuhlmann
Keyword(s):  
Unsupervised Segmentation ◽  
Sar Images ◽  
Interferometric Sar

Interferometric SAR imaging by transmitting stepped frequency chaotic noise signals

2015 ◽  
Author(s):  
Yunhua Zhang ◽  
Xiang Gu ◽  
Wenshuai Zhai ◽  
Xiao Dong ◽  
Xiaojin Shi ◽  
...  
Keyword(s):  
Sar Imaging ◽  
Stepped Frequency ◽  
Interferometric Sar

Information Theory-Based Approach for Contrast Analysis in Polarimetric and/or Interferometric SAR Images

2008 ◽  
Vol 46 (8) ◽  
pp. 2185-2196 ◽  
Author(s):  
J. Morio ◽  
P. Refregier ◽  
F. Goudail ◽  
P.C. Dubois-Fernandez ◽  
X. Dupuis
Keyword(s):  
Information Theory ◽  
Sar Images ◽  
Contrast Analysis ◽  
Interferometric Sar

Noise filtering of interferometric SAR images

1994 ◽  
Author(s):  
Jong-Sen Lee ◽  
Thomas L. Ainsworth ◽  
Mitchell R. Grunes ◽  
Raymond M. Goldstein
Keyword(s):  
Noise Filtering ◽  
Sar Images ◽  
Interferometric Sar
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