Multi-layer Sparse Coding Based Ship Detection for Remote Sensing Images
With the development of remote sensing technology, it becomes possible for the detection and identification of targets from remote sensing images. In this paper, we propose a new method integrating the bottom-up and the top-down mechanisms for the ship detection in high resolution satellite images. We use the multi-layer sparse coding to extract the features of the RS images. Then, we get the ship candidate regions by calculating the global saliency map which may have ships in it. Deformable part model is used to extract the ship features and latent support vector machine is used for the ship identification. As demonstrated in our experiments, the proposed approach can effectively detect ship in remote sensing images.