Fusion of multiple features to produce a segmentation algorithm for remote sensing images

This letter presents an edge direction adaptive watershed segmentation method for remote sensing images. First, the maximum gradient value among different directions is chosen as the single band gradient value of the pixel, and a compound gradient value is then calculated based on the gradient value in each band. Second, the marker-based watershed segmentation is implemented to produce initial over-segmentation result to avoid under-segmentation. Finally, the adjacent objects with high similarity values are merged to reduce over-segmentation, which improves segmentation accuracy. The performance of the proposed method is validated on two satellite images. Experimental results show that, compared with the multi-resolution segmentation method embedded in the eCognition software and the traditional multi-band watershed segmentation method, the proposed method can decrease over-/under-segmentation and thus produce satisfactory segmentation results.