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

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.

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

Remote Sensing ◽

10.3390/rs13245010 ◽

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.

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Comparative Study of Speckle Noise Reduction Approaches for Interferometric Synthetic Aperture Radar Images

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.427-429.1735 ◽

2013 ◽

Vol 427-429 ◽

pp. 1735-1738 ◽

Cited By ~ 1

Author(s):

Yi Fei Chen ◽

Hua Ping Xu

Keyword(s):

Noise Reduction ◽

Phase Distribution ◽

Speckle Noise ◽

Phase Image ◽

Geometrical Parameters ◽

Terrain Model ◽

Radar Images ◽

Interferometric Sar ◽

Speckle Noise Reduction

Speckle noise appearing in the interferometric SAR (InSAR) phase image degrades the quality of interferogram seriously and makes interferogram reflect the scattering characteristics of the target inaccurately, reducing the capability of extracting DEM information of target areas. Therefore, speckle noise reduction plays a major role in InSAR processing by using interferogram filtering. First, according to a terrain model with the assumed geometrical parameters in InSAR system, the paper simulated an interferometric SAR phase image with noise, which can be characterized by the multilook phase distribution based on the circular Gaussian assumption [1]. Second, the paper explores three interferogram filtering algorithm to remove speckle noise: Goldstain filter, Rotating Kernel Transformation and Lee filter; the proper implementation of three methods is given. Last, the paper discusses about the performance comparatively based on experimental results and gives broad conclusions and presents recommendations.

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A novel two-step noise reduction approach for interferometric phase images

Optics and Lasers in Engineering ◽

10.1016/j.optlaseng.2019.03.008 ◽

2019 ◽

Vol 121 ◽

pp. 1-10 ◽

Cited By ~ 5

Author(s):

Yandong Gao ◽

Shubi Zhang ◽

Tao Li ◽

Li Guo ◽

Qianfu Chen ◽

...

Keyword(s):

Noise Reduction ◽

Interferometric Phase ◽

Phase Images ◽

Reduction Approach

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Efficient noise reduction for interferometric phase image via non‐local non‐convex low‐rank regularisation

IET Signal Processing ◽

10.1049/iet-spr.2015.0420 ◽

2016 ◽

Vol 10 (7) ◽

pp. 815-824 ◽

Cited By ~ 2

Author(s):

Xiao Mei Luo ◽

Zhi Yong Suo ◽

Qie Gen Liu ◽

Xiang Feng Wang

Keyword(s):

Noise Reduction ◽

Low Rank ◽

Phase Image ◽

Interferometric Phase ◽

Non Local

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An Absolute Phase Estimation Method for Interferometry Imagery

Journal of Engineering Technology and Applied Physics ◽

10.33093/jetap.2019.1.2.4 ◽

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.

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Monitoring of Agricultural Grasslands With Time Series of X-Band Repeat-Pass Interferometric SAR

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2015.2478120 ◽

2016 ◽

Vol 9 (8) ◽

pp. 3687-3697 ◽

Cited By ~ 17

Author(s):

Karlis Zalite ◽

Oleg Antropov ◽

Jaan Praks ◽

Kaupo Voormansik ◽

Mart Noorma

Keyword(s):

Time Series ◽

X Band ◽

Interferometric Sar

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A new technique for noise filtering of SAR interferometric phase images

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/36.718849 ◽

1998 ◽

Vol 36 (5) ◽

pp. 1456-1465 ◽

Cited By ~ 193

Author(s):

Jong-Sen Lee ◽

K.P. Papathanassiou ◽

T.L. Ainsworth ◽

M.R. Grunes ◽

A. Reigber

Keyword(s):

New Technique ◽

Noise Filtering ◽

Interferometric Phase ◽

Phase Images ◽

A New Technique

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Deceptive Jamming Detection for SAR Based on Cross-Track Interferometry

Sensors ◽

10.3390/s18072265 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2265 ◽

Cited By ~ 2

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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Application of the Wiener filter to magnetic profiling in the volcanic environment of Mt. Etna (Italy)

Annals of Geophysics ◽

10.4401/ag-3951 ◽

1996 ◽

Vol 39 (1) ◽

Author(s):

C. Del Negro

Keyword(s):

Synthetic Data ◽

Wiener Filter ◽

Magnetic Anomalies ◽

Fault System ◽

Volcanic Area ◽

Wiener Filters ◽

Mt Etna ◽

Band Pass ◽

Magnetic Profile ◽

Mean Square Error Criterion

The frequency-domain Wiener filtering was applied to magnetic anomalies in the volcanic area of Mt. Etna. This filter, under suitable conditions (additive noise, linear processing and mean-square error criterion), can furnish an effective tool for discriminating the geologic feature of interest (the signal) from the noise. The filter was first tested with synthetic data. Afterwards it was applied to a magnetic profile carried out across the principal fault system of the Mt. Etna volcano, that hosted the dykes feeding both the 1989 and the 1991-93 eruptions. The magnetic anomalies linked to the volcanic section and those linked to the contact between the clay basement and the lava coverage show significant spectral overlap. Thus by estimating the power spectrum of the signal, obtained resolving the forward problem, a least-squares Wiener filter has been designed. In such context, it was possible to verify the effectiveness of Wiener filters, whereas traditional band-pass filtering proved inadequate. In fact, analysis of the noise showed that all the meaningful components of the observed magnetic field were resolved. The results put further constraints on location and geometry of the shallow plumbing system of Mt. Etna.

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