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For insufficient information of imaging spectrum with high spatial resolution, detailed imaging information, reduction of mixed pixels, increase of pure pixels and problems of image characteristic extraction and model classification produced from this, we provide a classifier model of a united spectrumspatial multicharacteristic based on SVM, and use this model to finish the image classification. The model completely uses the multicharacteristic information, and overcomes the overfitting problems produced by accumulating highdimensional characteristics. The model includes three classifications of spectrumspatial characteristics, namely spectral characteristicsspectral characteristic of multiscale morphology, spectral characteristicsphysical characteristics of underlaying surfaces of multiscale morphology and spectral characteristicsfeatures spatial extension characteristics of multiscale morphology. Firstly the three classifications of spectrumspatial characteristics are classified through SVM, then carries out the probability fusion for the classification results based on the pixels to obtain the final image classification results. This article respectively uses WorldView2 image and ROSIS image to experiment, and the results show that the model has better classification effect compared with VSSVM algorithm.
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