中文摘要：

精确的光谱表征是遥感专题地物信息提取的重要前提。针对不同水体光谱之间特征差异性，给水体信息全局光谱表征带来不确定性，提出了基于局部端元光谱表征的各类水体自适应提取方法。首先通过全局光谱指数计算实现水体的初步识别；然后，建立局部专题地物目标区，进行PPI计算提取局部水体端元；第三，通过计算局部区域内水体端元光谱相似度，统计光谱相似度直方图；最后，分析直方图分布特征，选择初始分割阈值，通过逐步迭代自动调整阈值达到最佳阈值选择，实现局部水体单元的自适应高精度提取。通过不同类型湖泊水体提取实验表明，该方法要优于传统的全局水体光谱指数阈值分割法，能够准确、自动地提取遥感影像上水体分布信息，几乎不受水体光谱特征差异的影响。

英文摘要：

Precise spectral characterization is fundamental for thematic information extraction. Because different types of water have different spectral features, which result in the difficulty of automatic retrieving water information precisely from the whole film. The present paper explored a new approach to water adaptive extraction based on local end member spectral characterization （LESC）. Firstly, through the spectral index calculation the primary water identification was achieved. Secondly, through spatial analysis and automatic end member extraction, we can get the water end member in part of region. Thirdly, according to the end member spectral, we can calculate local end member spectral similarity and histogram of similarity. Finally, through the histo- gram spectral analysis the optimal segmentation threshold was determined and according to the results the segmentation threshold was adjusted to fulfill water information extracting automatically and accurately. Experiments results show that through local end member spectral characterization the precision of extraction result can be promoted. The proposed method can extract all types of water information precisely and is not affected by different spectral feature.