Title: A novel algorithm for image denoising based on unscented Kalman filtering

Authors: Ruoqing Wang; Sufei Li; Ercan E. Kuruoglu

Addresses: School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University and Georgia Institute of Technology, Shanghai Campus, Shanghai, 200240, China ' School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University and Georgia Institute of Technology, Shanghai Campus, Shanghai, 200240, China ' ISTI-CNR, Italian National Council of Research, Pisa 56041, Italy

Abstract: 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.

Keywords: image denoising; unscented Kalman filter; UKF; 2D filtering; 2D non-symmetric half plane; noise removal; image quality.

DOI: 10.1504/IJICT.2013.054944

International Journal of Information and Communication Technology, 2013 Vol.5 No.3/4, pp.343 - 353

Received: 04 Dec 2012
Accepted: 10 Jan 2013
Published online: 19 Dec 2013 *

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