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Proceedings Paper

Multiscale directional filtering of noisy InSAR phase images
Author(s): Vishal M. Patel; Glenn R. Easley; Rama Chellappa
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Paper Abstract

In this work, we present a new approach for the problem of interferometric phase noise reduction in synthetic aperture radar interferometry based on the shearlet representation. Shearlets provide a multidirectional and multiscale decomposition that have advantages when dealing with noisy phase fringes over standard filtering methods. Using a shearlet decomposition of a noisy phase image, we can adaptively estimate a phase representation in a multiscale and anisotropic fashion. Such denoised phase interferograms can be used to provide much better digital elevation maps (DEM). Experiments show that this method performs significantly better than many competitive methods.

Paper Details

Date Published: 13 April 2010
PDF: 9 pages
Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 770308 (13 April 2010); doi: 10.1117/12.849576
Show Author Affiliations
Vishal M. Patel, Univ. of Maryland, College Park (United States)
Glenn R. Easley, Univ. of Maryland, College Park (United States)
System Planning Corp. (United States)
Rama Chellappa, Univ. of Maryland, College Park (United States)


Published in SPIE Proceedings Vol. 7703:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
Harold H. Szu; F. Jack Agee, Editor(s)

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