Classification of Polarimetric-SAR data with neural network using combined features extracted from scattering models and texture analysis

Katmoko Ari Sambodo and Aniati Murni and Mahdi Kartasasmita (2007) Classification of Polarimetric-SAR data with neural network using combined features extracted from scattering models and texture analysis. International journal of remote sensing and earth sciences, 4: 1. pp. 1-17. ISSN 0216-6739

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Abstract

This paper shows a study on an alternative method for classification of polarimetric-SAR data. The method is designed by integrating the combined features extracted from two scattering models (ie., Freeman decomposition model and Cloude decomposition model) and textural analysis with distribution-free neural network classifier. The neural network classifier (wich is based on a feed- forward back-propagation neural network architecture) properly exploits the information in the combined features for providing high accuracy classification results. The effectiveness of the proposed method is demonstrated using E-SAR polarimetric data acquired on the area of Penajam, East Kalimantan, Indonesia.

Item Type: Article
Uncontrolled Keywords: Polarimetric-SAR, scattering model, Freeman decomposition, Cloude decomposition, texture analysis, feature extraction, classification, neural networks, neural network models
Subjects: Taksonomi LAPAN > Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Pemanfaatan Penginderaan Jauh > Pengolahan Data > Klasifikasi
Divisions: LAPAN > Deputi Penginderaan Jauh > Pusat Pemanfaatan Penginderaan jauh
Depositing User: - Aullya -
Date Deposited: 24 Oct 2023 00:36
Last Modified: 24 Oct 2023 00:36
URI: https://karya.brin.go.id/id/eprint/20640

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