Image segmentation has been an mi portant research area in miage analysis and interpretation. An ideal segmentation strategy of remotely sensed data should considerproblems of over-segmentation and under-segmentation smi ultaneously and find a good tradeoffbetween them.In thispaper,miage segmentation for IKONOS multispectral data is investigated by using techniques of mathematical morphology, and a novelhybrid segmentation algorithm is proposed by combining both edge and texture featuresof mi ages. Based on theK-L transform of multispectral data, edge features are detected by morphological multiscale andmultidirection gradient algorithms, and mi age objects aremarked throughmorphological filtering and localvariance features extracting. Finally, themarkercontrolledwatershed algorithm is mi plemented. The results indicate that the performance of the proposed algorithm is superior to the gradientbased watershed segmentation. Moreover, this approach ismore suitable forhigh resolution remotely sensed data to overcome over-segmentation and underseg mentation problems effectively.