摘要
在对常规雷达数据特征与地物分类研究的基础上,重点研究双极化SAR图像的目标分解方法,并基于神经网络将分解后得到的极化信息与常规雷达数据有机结合应用于植被的分类研究。结果表明,多种极化信息能够获取更多的地物信息,极大地提高了植被识别和分类能力。
Based on the research of the conventional radar data features and surface features classification, this paper mainly studies the target decomposition method of dual polarization SAR image,and organically combines the decomposition informa-tion of polarization with conventional radar data, based on the neural network, to be used in vegetation classification, which greatly enhances the ability of vegetation identification and classification ability.
出处
《遥感信息》
CSCD
2013年第2期106-109,115,共5页
Remote Sensing Information
基金
中国地质调查局项目(1212010761502)
关键词
双极化SAR目标分解
神经网络
植被分类
Dual-polarisation SAR
target decomposition
neural network
vegetation classification
