基于数学形态学的IKONOS多光谱图像分割方法研究

利用数学形态学方法,研究与探讨了IKONOS多光谱图像的分割技术.提出一种结合图像边缘特征和纹理特征的混合分割新算法.在高分辨率多光谱遥感图像K-L变换的基础上,采用多尺度多方向形态学梯度算子提取边缘特征.应用数学形态学滤波及局部方差统计特征对图像对象进行标记,最后采用强制最小过程,进行标记控制的分水岭分割.研究结果表明,提出的分割算法优于仅利用边缘特征的分水岭分割算法,同时,该算法能较好地解决分割过程中存在的过分割与欠分割问题,是一种适合高分辨率多光谱遥感图像的分割算法.

Mathematical Morphological Segmentation of IKONOS Multispectral Data

Image segmentation has been an mi portant research area in mi age analysis and interpretation. An ideal seg- mentation strategy of remotely sensed data should considerproblems ofover-segmentation and under-segmentation smi ulta- neously and find a good tradeoffbetween them. In thispaper, mi age segmentation for IKONOSmultispectraldata is inves- tigated by using techniques ofmathematicalmorphology, and a novelhybrid segmentation algorithm is proposed by combi- ning both edge and texture featuresof mi ages. Based on theK-L transform ofmultispectraldata, edge features are detected bymorphologicalmultiscale andmultidirection gradient algorithms, and mi age objects aremarked throughmorphological filtering and localvariance features extracting. Finally, themarkercontrolledwatershed algorithm is mi plemented. The re- sults indicate that the performance of the proposed algorithm is superior to the gradientbasedwatershed segmentation. Mo- reover, this approach ismore suitable forhigh resolution remotely sensed data to overcome over-segmentation and under- segmentation problems effectively.