雷达科学与技术2021，Vol.19Issue(5)：539-551,557,14.DOI:10.3969/j.issn.1672-2337.2021.05.010
深度学习在极化SAR图像分类上的应用综述
A Survey:the Application of Deep Learning in PolSAR Image Classification
摘要
Abstract
Polarimetric synthetic aperture radar (PolSAR)is one of the most advanced and important envi-ronmental monitoring techniques owing to its all-time and all-weather observation character and strong capability to offer abundant and high-resolution target information.PolSAR image classification has been extensively inves-tigated and applied in recent years.Specifically,the booming of deep learning greatly accelerated the development of PolSAR image classification.This paper provides a survey on the application of deep learning in classifying PolSAR images,where the utilization of different categories of deep learning-based methods,including super-vised,unsupervised,semisupervised and active learning approaches are reviewed.In addition,we analyze the current challenges and future trends in this research topic.关键词
综述/极化SAR/图像分类/深度学习Key words
survey/polarimetric synthetic aperture radar (PolSAR)/image classification/deep learning分类
信息技术与安全科学引用本文复制引用
毕海霞,魏志强..深度学习在极化SAR图像分类上的应用综述[J].雷达科学与技术,2021,19(5):539-551,557,14.基金项目
国家自然科学基金(No.61806162) （No.61806162）
