A new phase unwrapping method based on region recognition and region expansion

This chapter presents a new phase unwrapping algorithm for the 3D Interferometric Synthetic Aperture Radar (3D InSAR) volumes. The proposed approach is based on the relationship between the gradient vectors of the observed wrapped phase and the true phase respectively, when the Itoh condition is satisfied. Since this relationship is violated by the residue pixels in the observed wrapped phase, a general problem formulation which takes into account the estimation error due to these residue values is proposed. This approach exploits the temporal inter correlation between the interferometric frames within a compressive sensing framework. The 3D discrete curvelet transform is used in order to ensure a suitable sparse representation of the phase volume. The performance of the proposed 3D phase unwrapping algorithm is tested on simulated and real SAR 3D datasets

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3D InSAR Phase Unwrapping within the Compressive Sensing Framework

Advances in Geospatial Technologies - Handbook of Research on Geographic Information Systems Applications and Advancements ◽

10.4018/978-1-5225-0937-0.ch005 ◽

2017 ◽

pp. 125-157

Author(s):

Wajih Ben Abdallah ◽

Riadh Abdelfattah

Keyword(s):

Compressive Sensing ◽

General Problem ◽

Estimation Error ◽

Curvelet Transform ◽

Problem Formulation ◽

Phase Unwrapping ◽

Interferometric Synthetic Aperture Radar ◽

Phase Volume ◽

The Relationship ◽

New Phase

This chapter presents a new phase unwrapping algorithm for the 3D Interferometric Synthetic Aperture Radar (3D InSAR) volumes. The proposed approach is based on the relationship between the gradient vectors of the observed wrapped phase and the true phase respectively, when the Itoh condition is satisfied. Since this relationship is violated by the residue pixels in the observed wrapped phase, a general problem formulation which takes into account the estimation error due to these residue values is proposed. This approach exploits the temporal inter correlation between the interferometric frames within a compressive sensing framework. The 3D discrete curvelet transform is used in order to ensure a suitable sparse representation of the phase volume. The performance of the proposed 3D phase unwrapping algorithm is tested on simulated and real SAR 3D datasets

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Least Squares Phase Unwrapping Algorithm Based on Topographic Factors

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.105-107.1876 ◽

2011 ◽

Vol 105-107 ◽

pp. 1876-1879

Author(s):

Wei Ke Liu ◽

Gou Lin Liu ◽

Xiao Qing Zhang

Keyword(s):

Least Squares ◽

Weighted Least Squares ◽

Phase Unwrapping ◽

Local Phase ◽

Complex Signals ◽

Topographic Factors ◽

Interference Fringes ◽

Phase Images ◽

New Phase ◽

Accuracy And Stability

The phase of complex signals is wrapped since it can only be measured modulo-2; unwrapping searches for the 2-combinations that minimize the discontinuity of the unwrapped phase, as only the unwrapped phase can be analyzed and interpreted by further processing. Weighted least squares phase unwrapping algorithm could avoid errors transmission in the whole phase images, but it could not avoid defect and overlay of interference fringes caused by topographic factors. Therefore, a new phase unwrapping and weights choosing method based on local phase frequency estimate of topographic factors was presented. Experiments show it is an efficient phase unwrapping method which well overcome the defect of under-estimate slopes by least squares algorithm, and has higher accuracy and stability than other methods.

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