Polarimetric SAR Despeckling With Convolutional Neural Networks

• Published in: IEEE transactions on geoscience and remote sensing Vol. 60; pp. 1 - 12
• Main Authors: Tucker, David, Potter, Lee C.
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additives; Artificial neural networks; Convolutional neural networks (CNNs); Covariance matrices; Covariance matrix; Deep learning; Neural networks; Polarimetry; Radar imaging; Radar polarimetry; SAR (radar); Scattering; Speckle; Synthetic aperture radar; synthetic aperture radar (SAR); Task analysis

Coherent imaging systems such as synthetic aperture radar (SAR) are subject to speckle, the reduction of which is an active area of study. Methods based on deep convolutional neural networks (CNNs) have recently demonstrated state-of-the-art performance in the removal of additive noise from natural...