Phase Unwrapping for InSAR using convex feasible model

In this paper, we proposed a complete scheme for phase retrieval under the framework of convex feasible models. The scheme is composed of two steps: the phase unwrapping and denoising. At first, we proposed a novel phase unwrapping method called Ideal Unwrapper (IU). Afterwards, to solve the rest de...

Full description

Saved in:
Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 6; pp. 3233 - 3237
Main Authors Liao, M., Wang, J.Y., Chen, W.F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Alternating Projection
Automation
Bayesian methods
Computer science
Convex Feasible
Cybernetics
Denoising
Electronic mail
Hilbert space
Iterative algorithms
Machine learning
Noise reduction
Phase Retrieval
Phase Unwrapping
Projections onto Convex Sets
Synthetic aperture radar interferometry
Online AccessGet full text

Cover

More Information
Summary:In this paper, we proposed a complete scheme for phase retrieval under the framework of convex feasible models. The scheme is composed of two steps: the phase unwrapping and denoising. At first, we proposed a novel phase unwrapping method called Ideal Unwrapper (IU). Afterwards, to solve the rest denoising problem, the theory of convex feasible is introduced. In addition, the convex sets for the Projection Onto Convex Sets (POCs) denoising, which might preserve the given arbitrary feature areas perfectly, are also constructed. Finally, numerical results are also illustrated to show the virtues of the proposed scheme. Especially, the proposed Ideal Unwrapper shows its powerful efficiency in Unwrapping two-dimensional phase images with little computational burden by comparing with the newly proposed Graph Cut method.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212778