Int. J. of Information and Communication Technology   »   2013 Vol.5, No.3/4

 

 

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

 

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

 

Submission date: 01 Dec 2012
Date of acceptance: 10 Jan 2013
Available online: 17 Jun 2013

 

 

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