SAR IMAGE SHIP DETECTION BASED ON VISUAL ATTENTION MODEL

This paper proposes a novel Synthetic Aperture Radar (SAR) image ship detection method based on human visual attention mechanism. Firstly, we obtain water segmentation image by combining the bottom-up and the top-down visual attention mechanisms. Secondly, we detect ship targets based on bottom-up the visual attention mechanism. The interested regions are extracted by measuring the visual conspicuity of each water regions. Then, the ships targets are detected in the interested regions by the k-means clustering algorithm. Finally, real SAR image is used to test our algorithm. Besides, we analysis the ship detection results using different band. The experiment results indicate that our algorithm can effectively detect ship targets from SAR images and C-band is superior to L-band in SAR image ship detection.