High density impulse noise removal based on the total observation kernel element for image sequences

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Fitri Utaminingrum, Keiichi Uchimura, Gou Koutaki

2014 Journal of Information Processing Vol. 22 Issue 4 Article Cited by 1

Abstract

Several different methods for impulse noise removal in image sequences have been proposed. However, all of them are not successful in removing high density of impulse noise. Hence, this paper proposes a filtering method for reducing high density impulse noise in the image sequences. We use three windows with size 3 × 3 to obtain a new window with similar size. Three windows are taken from the next-frame, current frames and previous frames. The recursive window is applied in the current frames. The filtering process uses decision-based method. Meanwhile, a pixel for replacing the noisy pixel is calculated from a new window based on weighting method. Our experimental results show that the proposed method can not only reduce the high impulse noise in image sequences well, but also preserve more details and textures. © 2014 Information Processing Society of Japan.

Affiliations

Computer Science and Electrical Engineering, Graduate School of Science and Technology, Kumamoto University, Chuoku, 860-8555, Kumamoto, Japan; Brawijaya University, Jl. Veteran No.8 Malang, East Java, 65145, Indonesia; Priority Organization for Innovation and Excellence, Kumamoto University, Kumamoto, 860-8555, Japan