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

Prashanth Reddy Marpu; Kun-Shan Chen; Jon Alti Benediktsson

doi:10.1117/12.898008

26 October 2011 Spectral-spatial classification of polarimetric SAR data using morphological attribute profiles

Prashanth Reddy Marpu, Kun-Shan Chen, Jon Alti Benediktsson

Proceedings Volume 8180, Image and Signal Processing for Remote Sensing XVII; 81800K (2011) https://doi.org/10.1117/12.898008
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

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.

Citation Download Citation

Prashanth Reddy Marpu, Kun-Shan Chen, and Jon Alti Benediktsson "Spectral-spatial classification of polarimetric SAR data using morphological attribute profiles", Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII, 81800K (26 October 2011); https://doi.org/10.1117/12.898008

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