Separable Image Denoising Based on the Relative Intersection of Confidence Intervals Rule

Article type: Research Article

Authors: Lerga, Jonatan | Sucic, Victor | Vrankić, Miroslav

Affiliations: Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia, e-mail: jlerga@riteh.hr, vsucic@riteh.hr, mvrankic@riteh.hr

Abstract: In this paper we have proposed a novel method for image denoising using local polynomial approximation (LPA) combined with the relative intersection of confidence intervals (RICI) rule. The algorithm performs separable column-wise and row-wise image denoising (i.e., independently by rows and by columns), combining the obtained results into the final image estimate. The newly developed method performs competitively among recently published state-of-the-art denoising methods in terms of the peak signal-to-noise ratio (PSNR), even outperforming them for small to medium noise variances for images that are piecewise constant along their rows and columns.

Keywords: relative intersection of confidence intervals (RICI) rule, image restoration, image denoising, adaptive filters, adaptive signal processing

Journal: Informatica, vol. 22, no. 3, pp. 383-394, 2011