Spectral-spatial classification of polarimetric SAR data using morphological attribute profiles

机译：使用形态学属性谱的极化SAR数据的光谱空间分类

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Morphological profiles (MPs) have been effective tools to fuse spectral and spatial information for the classification of remote sensing data. However, the previous applications have been limited to the multi-/ hyper-spectral data analysis. In this study, the application of morphological profiles is extended for the classification of polarimetric synthetic aperture radar (POLSAR) data. The MPs are constructed with the diagonal elements of the covariance matrix and the features derived from the eigenvalue decomposition method. The resulting extended morphological profile (EMP) which is a stack of all the MPs of various features is used for supervised classification of the images using a support vector machine (SVM) classifier. It is shown that significant improvements in classification accuracies can be achieved by using the profiles.

机译：形态特征（MP）是融合光谱和空间信息以进行遥感数据分类的有效工具。但是，先前的应用仅限于多光谱/高光谱数据分析。在这项研究中，形态学轮廓的应用扩展到极化合成孔径雷达（POLSAR）数据的分类。 MP由协方差矩阵的对角元素和特征值分解方法得出的特征构成。使用支持向量机（SVM）分类器，将得到的扩展形态学特征（EMP）（具有各种功能的所有MP的堆栈）用于图像的监督分类。结果表明，通过使用配置文件可以显着提高分类精度。

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来源
《Image and signal processing for remote sensing XVII》|2011年|p.81800K.1-81800K.6|共6页
会议地点 Prague(CZ)
作者
Prashanth Reddy Marpu; Kun-Shan Chen; Jon Atli Benediktsson;
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作者单位

Department of Electrical and Computer Engineering, University of Iceland, 101 Reykjavik, Iceland.;

Center for Space and Remote Sensing Research, National Central University, Chung-Li, Taiwan 320, R.O.C.;

Department of Electrical and Computer Engineering, University of Iceland, 101 Reykjavik, Iceland.;

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原文格式 PDF
正文语种 eng
中图分类遥感技术;
关键词
POLSAR; morphological profile; morphological attribute profile; classification;

机译：波兰形态形态属性概况分类;

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专利

1. Terrain classification based on spatial multi-attribute graph using Polarimetric SAR data [J] . Liu Hongying, Yang Shuyuan, Gou Shuiping, Applied Soft Computing . 2018,第期

机译：基于使用偏振SAR数据的空间多属性图的地形分类
2. A novel spectral-spatial classification technique for multispectral images using extended multi-attribute profiles and sparse autoencoder [J] . Teffahi Hanane, Yao Hongxun, Chaib Souleyman, Remote sensing letters . 2019,第1a3期

机译：使用扩展的多属性配置文件和稀疏自动编码器的多光谱图像光谱空间分类新技术
3. An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images [J] . Bhardwaj Kaushal, Patra Swarnajyoti ISPRS Journal of Photogrammetry and Remote Sensing . 2018,第APRa期

机译：一种用于高光谱图像光谱空间分类的属性配置文件中最佳特征选择的无监督技术
4. Spectral-spatial classification of polarimetric SAR data using morphological attribute profiles [C] . Prashanth Reddy Marpu, Kun-Shan Chen, Jon Atli Benediktsson Image and Signal Processing for Remote Sensing . 2011

机译：使用形态属性配置文件的偏振SAR数据的光谱空间分类
5. The application of maximum entropy density estimation to the classification of short vegetation using multifrequency, polarimetric SAR. [D] . Kouskoulas, Yanni A. 2001

机译：最大熵密度估计在短频植被分类中的应用-多频极化SAR。
6. Assessment of GF-3 Polarimetric SAR Data for Physical Scattering Mechanism Analysis and Terrain Classification [O] . Junjun Yin, Jian Yang, Qingjun Zhang 2017

机译：用于物理散射机理分析和地形分类的GF-3极化SAR数据评估
7. PARALLEL IMPLEMENTATION OF MORPHOLOGICAL PROFILE BASED SPECTRAL-SPATIAL CLASSIFICATION SCHEME FOR HYPERSPECTRAL IMAGERY [O] . B. Kumar, O. Dikshit 2016

机译：基于形态剖面的高光谱图像光谱 - 空间分类方案的并行实现
8. Target Classification Using SAR (Synthetic Aperture Radar) Polarimetric Data. [R] . Callaghan, A. P. 1989

机译：利用saR（合成孔径雷达）极化数据进行目标分类。

Spectral-spatial classification of polarimetric SAR data using morphological attribute profiles

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