A Novel Quality-Guided Two-Dimensional InSAR Phase Unwrapping Method via GAUNet

A Novel Quality-Guided Two-Dimensional InSAR Phase Unwrapping Method via GAUNet

Phase unwrapping (PU) has always been a critical and challenging step in interferometric synthetic aperture radar (InSAR) data processing. Inspired by existing research, i.e., the PGNet, we propose a novel quality-guided 2-D InSAR PU method via deep learning, and regard PU as a two-stage process. In...

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Bibliographic Details
Main Authors: Hai Wang, Jun Hu, Haiqiang Fu, Changcheng Wang, Zhenhai Wang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
2-D phase unwrapping (2-D PU)
ambiguity gradient
class imbalance
deep learning (DL)
interferometric synthetic aperture radar (InSAR)
quality-guided
Online Access:https://ieeexplore.ieee.org/document/9496097/

Internet

https://ieeexplore.ieee.org/document/9496097/

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