An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images. (August 2018)

• Record Type: Journal Article
• Authors: Varatharajan, R.; Vasanth, K.; Gunasekaran, M.; Priyan, M.; Gao, X.Z.
• Is Part Of: Computers & electrical engineering. Volume 70(2018)
• Page Start: 447
• Page End: 461
• Publication Date: 2018-08
• Subjects: Kriging interpolation -- Salt and pepper noise -- Semi variance -- Edge preservation; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.05.035
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Kriging interpolation is used for the removal of high density salt and pepper noise. The algorithm requires minimum of 3 number of pixels to interpolate else the window increases adaptively. Weights are calculated using semivariogram of non noisy pixels in the current processing window. The proposed algorithm removes the salt and pepper noise at very high noise densities by preserving the edges. Abstract: An adaptive decision based kriging interpolation technique for the removal of high density salt and pepper noise in images is proposed. The algorithm isolates the non noisy pixels and process only noisy pixel. The corrupted pixel is replaced by a value that is interpolated using the weights calculated using semi-variance between the corrupted pixels and the non noisy pixels in a confined neighborhood. The proposed technique requires at least three non noisy pixels in a current processing window, failing which the window increases adaptively. The proposed technique was found to exhibit good of quantitative evaluation and visual quality. The proposed algorithm also preserves image information with accurate noise detection when compared to many standard and existing algorithms. Graphical abstract: