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 |
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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 |