Computer and Robot Vision
Neural maps in remote sensing image analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Application of Self Organizing Maps to multi-resolution and multi-spectral remote sensed images
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
Comparison of Neural Classification Algorithms Applied to Land Cover Mapping
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
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In this paper, we present a Kohonen's Self Organizing Map for the land-cover classification of multi-spectral satellite images. In order to obtain an accurate segmentation we introduced as input for the network, in addition to the spectral data, some texture measures which gives a contribution to the classification of manmade structures. The texture features were extracted from high resolution images by means of Gray Level Co-occurrence Matrix (GLCM) and standard deviation. After clustering of SOM outcomes, we associated each cluster with a major land cover and compared them with prior knowledge of the scene analyzed. The results are encouraging as showed by the high values of the accuracy.