HIGH RESOLUTION POLSAR IMAGE CLASSIFICATION BASED ON GENETIC ALGORITHM AND SUPPORT VECTOR MACHINE
Article, Other literature type
Li, P. X.
Sun, W. D.
Lang, F. K.
- Publisher: Copernicus Publications
(issn: 2194-9034, eissn: 2194-9034)
TA1-2040 | T | TA1501-1820 | Applied optics. Photonics | Engineering (General). Civil engineering (General) | Technology
This paper focuses on backscattering mechanisms selection and supervised classification works for CETC38-X PolSAR image.
Thanks to the high radar resolution, many classes of man-made objects are visible in the images. So, land-use classification becomes
a more meanful application using PolSAR image, but it involves the selection of classifiers and backscattering mechanisms. In this
paper we apply SVM as the classifier and GA as the features selection method. Finally, after we find the best parameters and the
suitable polarimetric information, the overall accuracy is up to 97.49%. The result shows SVM is an effective algorithm compared to
Wishart and BP classifiers.