International Journal of Remote Sensing and Earth Sciences (IJReSES)
Vol 4,(2007)

CLASSIFICATION OF POLARIMETRIC-SAR DATA WITH NEURAL NETWORK USING COMBINED FEATURES EXTRACTED FROM SCATTERING MODELS AND TEXTURE ANALYSIS

Katmoko Ari Sambodo (Universitas Indonesia)
Aniati Murni (Universitas Indonesia)
Mahdi Kartasasmita (LAPAN)



Article Info

Publish Date
29 Sep 2010

Abstract

This paper shows a study on an alternative method for classification of polarimetric-SAR data. The method is designed by integrating the comined features extracted from two scattering models(i.e., freeman decomposition model and cloud decomposition model) and textural analysis with distribution-free neural network classifier. The neural network classifier (wich is based on a feedforward back-propagation neural network architecture) properly exploits the information in the combined features for providing high accuracy classification result. The effectiveness of the proposed method is demonstrated using E-SAR polarimetric data acquired on the area of Penajam, East Kalimantan, Indonesia. Keywords: Polarimetric-SAR, scattering model, freeman decomposition, Cloude decomposition, texture analysis, feature extraction, classification, neural networks.

Copyrights © 2007






Journal Info

Abbrev

ijreses

Publisher

Subject

Earth & Planetary Sciences

Description

International Journal of Remote Sensing and Earth Sciences (IJReSES) is expected to enrich the serial publications on earth sciences, in general, and remote sensing in particular, not only in Indonesia and Asian countries, but also worldwide. This journal is intended, among others, to complement ...