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Contextual Information Classification of Remotely Sensed Images
Oral Presentation
Authors
1electrical and computer engineering department. Tarbiat Modares university. Tehran. Iran (02182883373)
2Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
Abstract
This work proposes a multidisciplinary contextual information extraction and decision fusion approach for increasing the classification accuracy. It improves the image classification by integrating the results of various classifiers. The proposed method is implemented in three steps: 1) contextual feature extraction using four different feature extractors methods: a) Gray Level Cooccurrence Matrix, b) Gabor filters, c) Laplacian Gaussian filters and d) Gaussian Derivatives Functions; 2) classification of contextual features using four different classification rules (ML, Tree, KNN and SVM) by using only 2% of data for training the classifiers; and 3) finally, decision fusion using six decision fusion rules. The experimental results on real remotely sensed images have been presented.
Keywords
Proceeding Title [Persian]
Contextual Information Classification of Remotely Sensed Images
Authors [Persian]
Abstract [Persian]
This work proposes a multidisciplinary contextual information extraction and decision fusion approach for increasing the classification accuracy. It improves the image classification by integrating the results of various classifiers. The proposed method is implemented in three steps: 1) contextual feature extraction using four different feature extractors methods: a) Gray Level Cooccurrence Matrix, b) Gabor filters, c) Laplacian Gaussian filters and d) Gaussian Derivatives Functions; 2) classification of contextual features using four different classification rules (ML, Tree, KNN and SVM) by using only 2% of data for training the classifiers; and 3) finally, decision fusion using six decision fusion rules. The experimental results on real remotely sensed images have been presented.
Keywords [Persian]
contextual information، feature extraction، classification، decision fusion، remote sensing