Infrared Ship Target Image Smoothing Based on Adaptive Mean Shift

Abstract

Infrared (IR) image denoising is important for IR image analysis. In this paper, we propose a method based on adaptive range bandwidth mean shift for IR ship target image smoothing, aiming to effectively suppress noise as well as preserve important target structures. First, local image properties, including the mean value and standard deviation, are combined to build a salient region map, and a thresholding method is applied to obtain a binary mask on the target region. Then, we develop an adaptive range bandwidth mean shift method for image denoising. By associating the range bandwidth of the mean shift with local region saliency, we can adjust the bandwidth adaptively, thus to smooth the background region while preserving important target structures. Experimental results show that this method works well for IR ship target images with different backgrounds. It demonstrates superior performance for image denoising and target preserving, compared with some existing image denoising methods.