scholarly journals Enhancing Coherence Images for Coherent Change Detection: An Example on Vehicle Tracks in Airborne SAR Images

2021 ◽  
Vol 13 (24) ◽  
pp. 5010
Author(s):  
Horst Hammer ◽  
Silvia Kuny ◽  
Antje Thiele
Keyword(s):  
Change Detection ◽  
Sar Interferometry ◽  
Phase Image ◽  
Low Coherence ◽  
Interferometric Phase ◽  
Coherent Change Detection ◽  
Airborne Sar ◽  
Interferometric Sar ◽  
Favorable Conditions ◽  
High Coherence

In Synthetic Aperture Radar (SAR) interferometry, one of the most widely used measures for the quality of the interferometric phase is coherence. However, in favorable conditions coherence can also be used to detect subtle changes on the ground, which are not visible in the amplitude images. For such applications, i.e., coherent change detection, it is important to have a good contrast between the unchanged (high-coherence) parts of the scene and the changed (low-coherence) parts. In this paper, an algorithm is introduced that aims at enhancing this contrast. The enhancement is achieved by a combination of careful filtering of the amplitude images and the interferometric phase image. The algorithm is applied to an airborne interferometric SAR image pair recorded by the SmartRadar experimental sensor of Hensoldt Sensors GmbH. The data were recorded during a measurement campaign over the Bann B installations of POLYGONE Range in southern Rhineland-Palatinate (Germany), with a time gap of approximately four hours between the overflights. In-between the overflights, several vehicles were moved on the site and the goal of this work is to enhance the coherence image such that the tracks of these vehicles can be detected as completely as possible in an automated way. Several coherence estimation schemes found in the literature are explored for the enhancement, as well as several commonly used speckle filters. The results of these filtering steps are evaluated visually and quantitatively, showing that the mean gray-level difference between the low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%. Line extraction is then applied to the best enhancement. The results show that the tracks can be detected much more completely using the coherence contrast enhancement scheme proposed in this paper.

scholarly journals Interferometric SAR Phase Denoising Using Proximity-Based K-SVD Technique

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2684
Author(s):  
Chandrakanta Ojha ◽  
Adele Fusco ◽  
Innocenzo M. Pinto
Keyword(s):  
Noise Reduction ◽  
Synthetic Data ◽  
Sar Interferometry ◽  
Phase Image ◽  
Redundant Representations ◽  
X Band ◽  
Interferometric Phase ◽  
Phase Images ◽  
Mt Etna ◽  
Interferometric Sar

This paper addresses the problem of interferometric noise reduction in Synthetic Aperture Radar (SAR) interferometry based on sparse and redundant representations over a trained dictionary. The idea is to use a Proximity-based K-SVD (ProK-SVD) algorithm on interferometric data for obtaining a suitable dictionary, in order to extract the phase image content effectively. We implemented this strategy on both simulated as well as real interferometric data for the validation of our approach. For synthetic data, three different training dictionaries have been compared, namely, a dictionary extracted from the data, a dictionary obtained by a uniform random distribution in [ − π , π ] , and a dictionary built from discrete cosine transform. Further, a similar strategy plan has been applied to real interferograms. We used interferometric data of various SAR sensors, including low resolution C-band ERS/ENVISAT, medium L-band ALOS, and high resolution X-band COSMO-SkyMed, all over an area of Mt. Etna, Italy. Both on simulated and real interferometric phase images, the proposed approach shows significant noise reduction within the fringe pattern, without any considerable loss of useful information.

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>

Research on Motion Compensation for Airborne SAR Interferometry System

2013 ◽  
Vol 684 ◽  
pp. 414-419
Author(s):  
Yang Gao ◽  
Jin Song Du ◽  
Yi Yang Liu ◽  
Xin Bi
Keyword(s):  
Motion Compensation ◽  
Sar Interferometry ◽  
Motion Error ◽  
Radar Images ◽  
Digital Elevation ◽  
Interferometric Phase ◽  
Residual Motion ◽  
Airborne Sar ◽  
Elevation Model ◽  
Motion Error Compensation

Deviation from definitive flight path of a plane fixed a synthetic aperture radar (SAR) leads to inaccurate and defocused radar images, which has serious effect on the SAR interferometry (InSAR) processing. Therefore, the precise motion compensation (MOCO) for the airborne SAR interferometric data is the key to obtain high quality digital elevation model (DEM).The position and orientation system (POS)-based residual motion error compensation method is designed. Considering the precision of POS, there will be residual motion error after the POS-based MOCO, which have serious effect on the interferometric phase, especially the residual baseline errors. To solve the above problem, this paper proposed an enhanced multi-squint processing based model to estimate the residual baseline errors. This method can decrease the influence of data decorrelation and baseline error varying with range, and dramatically improve the measuring accuracy of InSAR.

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

scholarly journals Deceptive Jamming Detection for SAR Based on Cross-Track Interferometry

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2265 ◽  
Author(s):  
Qingqing Feng ◽  
Huaping Xu ◽  
Zhefeng Wu ◽  
Wei Liu
Keyword(s):  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Frequency Detection ◽  
Interferometric Phase ◽  
Deceptive Jamming ◽  
Jamming Detection ◽  
Novel Method ◽  
The Difference ◽  
Cross Track

Deceptive jamming against synthetic aperture radar (SAR) can create false targets or deceptive scenes in the image effectively. Based on the difference in interferometric phase between the target and deceptive jamming signals, a novel method for detecting deceptive jamming using cross-track interferometry is proposed, where the echoes with deceptive jamming are received by two SAR antennas simultaneously and the false targets are identified through SAR interferometry. Since the derived false phase is close to a constant in interferogram, it is extracted through phase filtering and frequency detection. Finally, the false targets in the SAR image are obtained according to the detected false part in the interferogram. The effectiveness of the proposed method is validated by simulation results based on the TanDEM-X system.

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