scholarly journals Filtering of Interferometric SAR Phase Images as a Fuzzy Matching-Pursuit Blind Estimation

Author(s):  
Bruno Aiazzi ◽  
Stefano Baronti ◽  
Massimo Bianchini ◽  
Alessandro Mori ◽  
Luciano Alparone
2002 ◽  
Author(s):  
Bruno Aiazzi ◽  
Luciano Alparone ◽  
Stefano Baronti ◽  
Massimo Bianchini

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2684
Author(s):  
Chandrakanta Ojha ◽  
Adele Fusco ◽  
Innocenzo M. Pinto

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.


2011 ◽  
Vol E94-B (12) ◽  
pp. 3614-3617
Author(s):  
Bin SHENG ◽  
Pengcheng ZHU ◽  
Xiaohu YOU

2010 ◽  
Vol 69 (19) ◽  
pp. 1681-1702
Author(s):  
V. V. Lukin ◽  
S. K. Abramov ◽  
A. V. Popov ◽  
P. Ye. Eltsov ◽  
Benoit Vozel ◽  
...  

2011 ◽  
Vol 30 (5) ◽  
pp. 1104-1108 ◽  
Author(s):  
Shui-ping Gou ◽  
Li-cheng Jiao ◽  
Xiang-rong Zhang ◽  
Yang-yang Li

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