Multi-Modal Ship Target Image Smoothing Based on Adaptive Mean Shift

In this paper, we propose an adaptive image smoothing method for infrared (IR) and visual ship target images, aiming to effectively suppress noise as well as preserve important target structures, thus benefiting image segmentation. First, by analyzing the specific features of ship target images, a block based method combining local region mean and standard deviation is developed to highlight ship target regions. It is helpful to distinguish the ship target region from the background. Then, by associating the range bandwidth with local image properties of the ship target region and the background region, we develop an adaptive range bandwidth mean shift filtering method for IR and visual ship target image smoothing. With this proposed method, we can obtain a small bandwidth for ship target region and a large one for the background region. Therefore, we can effectively smooth the background while preserving the details of the targets. Experimental results show that this method works well for IR and visual ship target images with different backgrounds. The method demonstrates superior performance for image smoothing and target preservation compared with the four well-known edge-preserving denoising methods, including the anisotropic diffusion filtering, the bilateral filtering, the propagation filtering, and the mean shift filtering with fixed range bandwidth.