Journal of Physical Chemistry & Biophysics
Open Access

Abstract

Graph-Based Feature Reduction for Three-Dimensional Gabor Filter in PolSAR Image Classification

Mohsen Darvishnezhad*

Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. In this paper, the goal is PolSAR image classification and also to introduce a method to obtain the best result for PolSAR image classification and recognition. In this article, we present the 3D-Gabor filters as a way in order to feature extraction of PolSAR images and get the best result with high accuracy for PolSAR image classification. Also, we prove that the 3D-Gabor filter approach can get higher accuracy than traditional methods for PolSAR images classification, but one of the most important challenges of 3D-Gabor filters is the number of features that are extracted from them. Therefore, by using 3D-Gabor filter we can't reach the optimal result because of the curse of dimensionality. So, to achieve the best results we propose a method to reduce the features that are extracted from 3D-Gabor filters. By using our proposed method, the features will be mapped to a new space with smaller dimensions. In the end, the experimental results indicate the superiority of the proposed method.

Published Date: 2021-12-16; Received Date: 2012-11-25