conference paper
Novel Features for Polarimetric SAR Image Classification by Neural Network
Kamran Ullah Khana, Jian Yanga
- aDepartment of Electronic Engineering, Tsinghua University, Beijing, China
International Conference on Neural Networks and Brain2006-04-28 5 citations8 references
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Abstract
This paper presents a set of effective features derived from the coherence matrix of polarimetric SAR data. Neural network is used as the classification engine. The maximum likelihood estimator (MLE) result is used as the reference to compare the result of the proposed method. It is demonstrated that the average classification accuracy by the proposed method is more than that by the MLE. The maximum overall efficiency obtained by the proposed method is 95.4%.