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如何全面、准确地度量和可视化表达信息处理中不确定性的程度和空间分布方式,是信息不确定性研究的关键问题之一。传统的度量方法(例如误差矩阵)是将以训练样本集为基础的度量作为总分类精度的度量,而我们需要估计模型对于“样本外数据”的性能。本文首先利用信息论和粗糙集理论等度量分类影像属性信息的不确定性,提出基于像元、目标和影像的信息不确定性度量指标;然后分别描述了基于不同度量指标的可视化表达方式,并对我国黄河三角洲地区的Landsat TM影像进行了分类信息不确定性度量和可视化表达实验。 更多还原

【Abstract】 The measurement and accurate visualization of the value and spatial distribution of uncertainty in remotely sensed image make up one of the key problems in the field of remote sensing.In the traditional fashions,e.g.,in error matrix,the measurements based on the training data are regarded as the measures of the overall accuracy of classification models.Nevertheless,we need to estimate their performance on "out-of-sample-data"-data that have not been used in constructing the models.In this paper,... 更多还原