期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B3b
页码：431-434
出版社：Copernicus Publications
摘要：Image segmentation is defined as partitioning an image into non-overlapping regions based on the intensity or texture. The active contour methods with comes from the basic ideas of Stochastic Motion and the Level Set Method provide an effective way for segmentation, in which the boundary of an object usually with large image gradient value is detected by an evolving curve. But, these methods have limitations due to the fact that real images may have objects with complex geometric structures and shapes, and are often corrupted by noise. Developing more robust and accurate active contour methods has been an active research area since the idea of the methods was proposed. In this paper, we propose a new active contour method and apply the method to remote sensing image segmentation. This new method uses combination of boundary-based modelling and region-based modelling. The new method is more efficient and effective, especially in detecting structures with noise
