Ship detection algorithm for optical remote sensing images

A ship detection algorithm was developed for general hardware platforms for optical remote sensing images. The system uses an adaptive threshold histogram-based segmentation technique for the land masking. Then, the sparseness of ships on the sea is used to develop an effective prescreening approach based on the tile statistical features with only the target-labeled tiles processed in the next step. A clutter rate coefficient is used to control the structural elements of the morphology Top-Hat operator for better background suppression. Finally, a pattern recognition method is used for discrimination. Tests show the effectiveness of this algorithm implemented on a hardware platform.