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Remote Sensing Image Classification Based on BP Neural
Network
Yu Bing
School of Water Resource and Environment, Hohai University, Nanjing, Jiangsu, China (210098)
Abstract
The traditional statistical classifier is suitable in making RS image classification in normal distribution with its low precition. After analyzing the principle and learning algorithms of BPNN, land use classification of BPNN is acquired by selecting optimized spectral data.The classification results are compared with the results obtained by Maximum Likelihood classifier. Experimental results show that BPNN is superior to the latter in the accuracy of classification.
Keywords: remote sensing,BP neural network,image classification,maximum likelihood classifier
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