1. 中国测绘科学研究院,北京,100830
2. 中国矿业大学环境与测绘学院,江苏,徐州,221116
3. 中国测绘科学研究院,北京,100830
4. 中国矿业大学环境与测绘学院,江苏,徐州,221116
纸质出版:2015
移动端阅览
闫丽丽, 张继贤, 高井祥, 等. 一种适合方位建筑物的基于物理散射模型的极化SAR影像四分量分解方法[J]. 电子学报, 2015,43(1):203-208.
YAN Li-li, ZHANG Ji-xian, GAO Jing-xiang, et al. Four-Component Model-Based Decomposition of Polarimetric SAR Data for Oriented Urban Buildings[J]. Acta Electronica Sinica, 2015, 43(1): 203-208.
闫丽丽, 张继贤, 高井祥, 等. 一种适合方位建筑物的基于物理散射模型的极化SAR影像四分量分解方法[J]. 电子学报, 2015,43(1):203-208. DOI: 10.3969/j.issn.0372-2112.2015.01.032.
YAN Li-li, ZHANG Ji-xian, GAO Jing-xiang, et al. Four-Component Model-Based Decomposition of Polarimetric SAR Data for Oriented Urban Buildings[J]. Acta Electronica Sinica, 2015, 43(1): 203-208. DOI: 10.3969/j.issn.0372-2112.2015.01.032.
针对走向与雷达飞行方向不平行的建筑物(简称为方位建筑物)
提出了一种基于物理散射模型的极化SAR影像四分量分解方法.该方法用于区分散射类型易混淆的方位建筑物和植被.本文首先对方位角补偿后的相干矩阵进行相位旋转;然后构造一种修正的体散射模型
该模型包含纯体散射模型和方位二面角散射模型;最后加入两个能量限制条件
有效避免了负能量像素点的出现.实验结果表明
与已有的四分量分解方法相比
提出的分解方法有效解决了方位建筑物被误识别为植被等体散射类型的问题且消除了负能量
有利于从植被中区分方位建筑物.
This paper presents an improvement to a four-component model-based decomposition scheme of polarimetric synthetic aperture radar (SAR) images for oriented urban buildings.Techniques to discriminate the ambiguity between oriented buildings and vegetation are proposed.First
phase rotation (PR) of the coherency matrix after orientation angle compensation (OAC) is derived to minimize the cross-polarization component.Second
an alternative volume scattering model with a criterion for pure randomness scatterers and/or oriented dihedral structures is introduced in the proposed decomposition.Finally
power constraints are appended to the scheme to prevent negative powers.It is shown that the oriented urban buildings are well distinguished as double bounce objects from vegetation areas compared to those from the existing four component decompositions and the negative powers are eliminated.
0
浏览量
2
下载量
6
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621