Study of Infrared Image Denoising Algorithm Based on Steering Kernel Regression Image Guided Filter

Abstract

Infrared image has the disadvantages of narrow dynamic range, low contrast and easy to be polluted by noise. For this reason, this paper proposes a new infrared image denoising method based on steering kernel regression image guided filter. In this method, the shape and size of the steering kernel are firstly determined according to the local gradient information of the image, and then the filtering weight is obtained by the steering kernel regression, which is used to modify the analysis window of image guided filtering. The experimental results show that the proposed method is better than the guided filter and the steering kernel regression algorithm. Compared with the traditional infrared image denoising algorithm, this method can retain the image details, and acquire better visual experience.