Image classification with spectral and texture features based on SVM

Geoinformatics（2010）

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摘要

In this paper, a three-step classification method is proposed for remote sensing images with the spectral and texture features based on the Support Vector Machine (SVM) classifier. The image is first segmented into regions with the spectral features. Then, texture features are extracted from each region by the undecimated wavelet transform. Third, the SVM is used to classify the image with these extracted texture features. A postprocessing method is also proposed to handle the small regions and anomalistic regions.

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关键词

geophysical techniques,image segmentation,spectral feature,image classification,support vector machine classifier,geophysical image processing,texture feature,wavelet transform,texture,remote sensing images,support vector machines,remote sensing,support vector machine,pixel,wavelet transforms,feature extraction

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