基于SPOT5影像自动提取水体的新方法

利用遥感影像进行自动化水体提取是一项富有挑战的任务。提出了一种GIS数据辅助下的可见光遥感影像水体自动提取方法，其核心是将影像分割、配准和变化检测集成为一体化处理流程检测水体。
利用水体在遥感影像上的显著特性，首先提出了基于多尺度视觉注意模型的疑似水体区域检测；然后对影像显著区域进行水平集分割处理，通过迭代的分割和配准一体化处理不断优化直至获得最优的分割和配准结果，其中改进的形状曲线相似度特征用于约束分割结果与GIS水体对象的匹配；最后，利用基于缓冲区的变化检测方法获取变化和未变化的水体对象，同时利用已知水体辐射特征与GIS地物的空间位置关系剔除非水体对象。采用3组不同分辨率的遥感影像和不同尺度的GIS数据进行实验，结果显示了本文方法在水体自动提取和变化检测中的有效性。

Satellite Remote Sensing of Earthquake,Volcano, Flood,Landslide and Coastal Inundation Hazards

Automatic water-body extraction from remote sensing images is a challenging problem. In this paper, a novel automatic water-body extraction technique is proposed for optical visible remote sensing images. It integrates image segmentation, image registration and change detection with GIS data as a whole process. A new iterative segmentation and registration strategy is also proposed. A multi-scale visual attention model is introduced to detect salient areas and a level-set segmentation algorithm is employed for image segmentation.
An improved shape curve similarity (ISCS) method is presented to constrain the matching of image segmentation objects and GIS-identified water-bodies. Furthermore, a buffer-based change detection algorithm was designed to obtain unchanged water-bodies and non-water objects were eliminated with the aid of GIS data and spectral features. Experiments were carried out on three sets of data.Results show that the proposed method was effective in rapid water body extraction and change detection.