Segmentation of High-Resolution Remote Sensing Image Based on Marker-Based Watershed Algorithm

Because of the particularity of high resolution remote sensing image such as Quickbird, the segmentation methods used in common video or image are unsuitable for high-resolution remote sensing image. In order to overcome the shortcomings of over-segmentation existing in watershed algorithm, we bring in a new method which is an improvement to the marker-based watershed algorithm. Firstly, the median filtering is carried out to the high-resolution remote sensing image to eliminate random noise in the image, and then gradients are obtained with mathematical morphology; finally, the maker-based watershed algorithm is applied to the gradients to segment the image. Segmentation experiments carried out for the Quickbird images with different kinds of land cover types, show that the method is efficient and it can avoid over-segmentation when the image texture is homogeneous, but it also has some limitations when the image texture is relatively complex.