基于模糊拓扑及多特征融合的遥感影像亚像元定位

项目名称： 基于模糊拓扑及多特征融合的遥感影像亚像元定位

项目编号： No.41201451

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 地理学

项目作者： 张华

作者单位： 中国矿业大学

项目金额： 25万元

中文摘要： 亚像元定位已成为定量遥感的研究热点。针对现有的亚像元定位模型定位精度不高、结果不确定性和不能同时处理LR和HR情况等问题。本项目拟研究基于模糊拓扑及多特征融合的遥感影像亚像元定位。包括：（1）针对亚像元定位的欠约束问题，利用隐半马尔科夫模型、小波纹理、数学形态学等方法提取影像的空间特征信息并进行优化、选择与组合，得到有利于亚像元定位的多特征组合信息，增加模型的约束条件，提高模型的可靠性；（2）利用模糊拓扑理论将面积较大的斑块、地物的边界、尺度小的线性地物及小于像元的地物探测出来，提供斑块形状及空间分布信息；（3）以探测出的地物空间分布信息为基础，针对不同结构类型的斑块，融合影像的多特征组合信息，构建不同的定位模型并对不同类型的斑块分别进行亚像元定位。模型兼顾了地物的结构特征，并可以同时处理HR和LR的情况，在一定程度上克服了现有亚像元定位算法的缺点，提供了可靠的亚像元定位模型。

中文关键词： 遥感；亚像元定位；模糊拓扑；空间特征；

英文摘要： Sub-pixel mapping has become a hot research topic of Quantitative Remote Sensing. Considering current sub-pixel mapping methods' shortcomings including lower accuracy, uncertainty and can not handle the coexistent of LR (lower resolution) and HR (high resolution) mapping, etc. The project will study sub-pixel mapping based on fuzzy topology and multi-feature fusion from remotely sensed data. The main content includes (1) As the sub-pixel mapping being an under constraint problem, Hidden Semi-Markov Model, Wavelet Texture, Mathematical Morphology, etc. are proposed to extract spatial features from remotely sensed data, and these features are further optimized, selected and combined to provide useful combination information for sub-pixel mapping. As a result, the constraints are increased for the sub-pixel mapping model and the reliability of the model is improved; (2) In order to provide patches' shapes and the spatial distribution information, Fuzzy Topology method is used to detect the larger sizes of patches, boundaries of surface features, small-scale linear and those surface features whose dimension is smaller than a pixel; (3) Based on the detected spatial distribution of the surface features, integrating the multi-features extracting from the remotely sensed data, different sub-pixel mapping models are bui

英文关键词： remote sensing；Sub-pixel mapping；Fuzzy topology；spatial feature；