Multi-layer sparse coding model-based ship detection for optical remote-sensing images

Ship detection plays an important role in remote-sensing image processing. In this article, we propose a multi-layer sparse coding model-based ship detection (MSCMSD) method, integrating bottom-up and top-down mechanisms, for ship detection with high-resolution remote-sensing images. The multi-layer sparse coding model was designed to reveal the way how information is processed by human visual system. It is adopted in MSCMSD to detect candidate regions containing ships before any further processing. To detect ships from candidate regions, an omnidirectional solution is also proposed for deformable parts model-based ship detection. As demonstrated in the experiments, MSCMSD can detect ships from optical remote-sensing images with a higher accuracy than other state-of-the-art algorithms.