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《ACTA SCICENTIARUM NATURALUM UNIVERSITIS PEKINESIS》 2000-06
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Satellite Image Classification Based on Fractal Dimension and Neural Networks

QIN Qiming\ LU Rongjian (Institute of Remote Sensing and GIS,Peking University,China,100871)  
It is a new approach to improve the accuracy of image classification in combining spectral feature with texture and structural features of ground objective on satellite image.Based on the recognizable characteristics of satellite image,it is introduced how to describe and capture texture and structural features of ground objective by the Discrete Fractional Brownian Motion model.Furthermore,neural networks are used for classification tool of satellite image.In classification spectral feature,texture and structural features of ground objective are used for the category of an IRS\|1C satellite image.The category result shows this approach is better than the maximum likelihood classifier.
【Fund】: 国家自然科学基金资助项目!(496 710 6 4)
【CateGory Index】: TP75
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