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Adaptive filtering method combined with quality map for InSAS interferogram
by
Huang, Pan
, Zhong, Heping
, Teng, Xiaojie
in
Adaptive filters
/ Algorithms
/ Conflicts of interest
/ Data processing
/ Digital Elevation Models
/ Methods
/ Noise control
/ Partial differential equations
/ Phase noise
/ Phase unwrapping
/ Real time
/ Registration
/ Signal quality
/ Sonar
/ Synthetic apertures
2022
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Adaptive filtering method combined with quality map for InSAS interferogram
by
Huang, Pan
, Zhong, Heping
, Teng, Xiaojie
in
Adaptive filters
/ Algorithms
/ Conflicts of interest
/ Data processing
/ Digital Elevation Models
/ Methods
/ Noise control
/ Partial differential equations
/ Phase noise
/ Phase unwrapping
/ Real time
/ Registration
/ Signal quality
/ Sonar
/ Synthetic apertures
2022
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Do you wish to request the book?
Adaptive filtering method combined with quality map for InSAS interferogram
by
Huang, Pan
, Zhong, Heping
, Teng, Xiaojie
in
Adaptive filters
/ Algorithms
/ Conflicts of interest
/ Data processing
/ Digital Elevation Models
/ Methods
/ Noise control
/ Partial differential equations
/ Phase noise
/ Phase unwrapping
/ Real time
/ Registration
/ Signal quality
/ Sonar
/ Synthetic apertures
2022
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Adaptive filtering method combined with quality map for InSAS interferogram
Journal Article
Adaptive filtering method combined with quality map for InSAS interferogram
2022
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Overview
The quality of interferogram, which is limited by various phase noise, will greatly influence the subsequent processes of interferometric synthetic aperture sonar (InSAS), such as phase unwrapping and digital elevation model (DEM) estimation. Therefore, phase filtering is an essential step in signal processing for InSAS. In this paper, an adaptive filtering method combined with quality map is proposed to suppress the phase noise while preserving the fringe edges. The main advantage of the new approach is the size of filtering window can be adaptively selected according to the quality map. A function between window size and quality map is established, which controls the strength of filtering. In the area of high quality, the window size is large to remove noise, otherwise, in the low quality area, the window size is small to keep edge details. The effectiveness of the proposed method is validated via some illustrative simulated experiment and the real InSAS data.
Publisher
John Wiley & Sons, Inc,Wiley
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