Robust SAR Image Despeckling by Deep Learning From Near-Real Datasets

Robust SAR Image Despeckling by Deep Learning From Near-Real Datasets

The inherent speckle in synthetic aperture radar (SAR) images significantly affects their potential usefulness, and its effective suppression is a challenging and nontrivial task. This article uses near-real SAR intensity datasets as the training data for the first time and proposes a robust deep le...

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Bibliographic Details
Main Authors: Jianjun Guan, Rui Liu, Xin Tian, Xinming Tang, Song Li
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Despecked
Generalized likelihood ratio test (GLRT)
near-real synthetic aperture radar (SAR) datasets
phase-guided deep despeckling Network (PGD2Net)
Online Access:https://ieeexplore.ieee.org/document/10368288/

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