国土资源遥感Issue(4)：37-41,5.
基于最小核值相似区算法的高分辨率遥感图像分割方法
Segmentation of the High Spatial Resolution Remotely Sensed Imagery Based on SUSAN
摘要
Abstract
The SUSAN (Smallest Univalue Segment Assimilating Nucleus) method is used to detect gradient features from QuickBird imagery, and then the imagery is segmented using marker - controlled WT ( Watershed Transform), and the segmentation result is satisfactory. The SUSAN method detects gradients well. It is not sensitive to noise and the values of the gradients are in a definite range and do not change with images, which offers convenience in selecting parameters in the later processes. The method is flexible because it is easy to choose the illumination threshold and the size of SUSAN matrix is not fixed. Based on the marker derived from both SUSAN gradients and NDVI, the gradients are modified using morphological grayscale reconstruction method, which efficiently constrains much local minima of the gradients and improves the segmentation precision.关键词
最小核值相似区算法( SUSAN)/分水岭变换(WT)/QuickBird图像/图像分割Key words
Smallest Univalue Segment Assimilating Nucleus (SUSAN) / Watershed Transform (WT) / QuickBird imagery/ Image segmentation分类
计算机与自动化引用本文复制引用
薛峭,赵书河..基于最小核值相似区算法的高分辨率遥感图像分割方法[J].国土资源遥感,2011,(4):37-41,5.基金项目
国家自然科学基金项目(编号:40501047)资助. （编号:40501047）
