Abstract:

As navigation marks have strong similarity among each other, a new method for detecting navigation marks in high-resolution remote sensing imagery is proposed. On the basis of segmenting the land and the water using  one-class support vector machine, the small targets within the water regions are detected and regarded as the candidate ones. The targets which satisfy the pixel intensity and the geometric feature of navigation marks will be saved and used for organizing correlative groups. If the relation coefficient between two navigation marks meets the given conditions, they are considered as one group, then the largest group is regarded as the group of navigation marks. Finally, the method is tested and verified with the QuickBird fusion 0.6 m imagery. With 82% navigation marks detected, the method has been proven to be effective in the experimental region.