Abstract
In this paper, a combination of artificial neural network (ANN)and genetic algorithm(GA) has been proposed as a method to obtain a high accuracy in classification of polarimetric SAR data. First we extracted 57 features based on decomposition algorithms and then the best features among inputted features by use of GA-ANN wereselected.The classification results of a data set, composed of different land cover elements, exhibited higher accuracy than maximum likelihood and Wishart classifier; moreover the input features were decreased to small numbers which contain sufficient information for classification of data set.
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Haddadi G., A., Sahebi, M. (2011). Combination of GA and ANN to High Accuracy of Polarimetric SAR Data Classification. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21501-8_26
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DOI: https://doi.org/10.1007/978-3-642-21501-8_26
Publisher Name: Springer, Berlin, Heidelberg
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