基于像斑的多光谱影像跨尺度分类研究  

Application of Decision Tree on Multispectral Images Based on Segment and Scale-Span Features

作　　者：林丽群[1] 舒宁[1,2] 龚龑[1] 肖俊[2] 

机构地区：[1]武汉大学遥感信息工程学院,武汉市430079 [2]武汉大学测绘遥感信息工程国家重点实验室,武汉市430079

出　　处：《武汉大学学报（信息科学版）》2009年第1期40-43,共4页Geomatics and Information Science of Wuhan University

基　　金：国家973计划资助项目(2006CB701303,2004CB318206);国家自然科学基金资助项目(40371079)

摘　　要：提出了一种新的多尺度像斑模型,充分利用多尺度像斑模型所提供的尺度纵向信息,并结合决策树的分类方法来实现跨尺度分类,而不直接进行最佳尺度选择。实验结果证明,跨尺度方法较单一尺度分类能更准确地区分地物,从而提高分类精度。Existing classification methods, based on the homogeneous-region, mostly involve the best segmentation criterion choice. Using the so-called best scale to classify the multiscale objects defined by human subjectivity, the paper doesn＇t think it is the best way for classification. So the paper proposes a new multi-scale homogeneous-region model, fully using the longitudinal information which the homogeneous-region model provides, and adopting the scale-span classification method based on decision tree to improve the accuracy, without selecting the best-scale data. The result shows this method can distinguish objects accurately and improve the precision than sole scale classification.

关 键 词：多光谱 影像分割 像斑分析 决策树 多尺度 

分 类 号：P237.3[天文地球—摄影测量与遥感]