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中文摘要：
在分析应用对象化分析方法改进高空间分辨率遥感影像分类技术的基础上,提出了应用多层次的迭代模型改进分类流程,在自适应的迭代过程中有效地结合主导类别选择、高级对象特征计算、基于互信息的特征选择等技术提高对象化方法中丰富的影像特征的利用效率,同时,有机结合像素级特征信息弥补对象化特征。通过对SPOT5影像与航空影像两种数据源的土地覆盖分类的实验表明,该方法可以有效地提高分类精度。
英文摘要：
While spectral analysis of images has yielded satisfactory results,they may not be enough to extract features from high spatial resolution satellite data.A novel iterative classification approach is proposed,which based on object-oriented technologies.This approach makes use of both pixel spectral features and object features through an iterative model to improve the accuracy of classification.Some adaptive techniques are used for each iteration,which are leading class selection,advanced object-based feature calculating,feature selection based on mutual information.The experiment of land cover classification on SPOT5 image and aerial photography shows this approach produces higher classification accuracy than normal object-oriented classification.
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