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Paper Details

Optimized Neural Network for Classification of Multispectral Images

Optimized Neural Network for Classification of Multispectral Images

Rajesh K. Agrawal, Dr. Narendra G. Bawane

Journal Title:ACEEE International Journal on Signal And Image Processing

The proposed work involves the multiobjective PSO based optimization of artificial neural network structure for the classification of multispectral satellite images. The neural network is used to classify each image pixel in various land cove types like vegetations, waterways, man-made structures and road network. It is per pixel supervised classification using spectral bands (original feature space). Use of neural network for classification requires selection of most discriminative spectral bands and determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) to determine discriminative spectral bands and the number of hidden layer node simultaneously. The result obtained using such optimized neural network is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of all classifiers is evaluated quantitatively using Xie-Beni and â indexes. The result shows the superiority of the proposed method.