A novel algorithm for image denoising based on unscented Kalman filtering

This paper presents a noise removal algorithm based on unscented Kalman filtering in order to improve image quality. We first analysed the characteristics of the background noise, and then discussed the unscented Kalman filter (UKF). After that, one-dimensional unscented Kalman filtering, and two-dimensional non-symmetric half plane (NSHP) support image model based on two-dimensional unscented Kalman filtering are introduced. Experimental results show that as an adaptive method, the algorithm reduces the noise while retaining the image details, and two-dimensional NSHP model performs better than one-dimensional UKF algorithm. Therefore, UKF together with its two-dimensional NSHP implementation have efficacy for noise removal of images.