Title: Image denoising based on sub-image restoration through threshold optimisation

Authors: Somnath Mukhopadhyay; J.K. Mandal

Addresses: Department of Computer Science and Engineering, University of Kalyani, West Bengal 741235, India ' Department of Computer Science and Engineering, University of Kalyani, West Bengal 741235, India

Abstract: This paper proposed a novel approach for detection and filtering of impulses in digital images through median filtering based on optimisation through particle swarm optimisation (PSO) technique. The input image is logically partitioned into 5 × 5 sub images. Two restored versions are generated through proposed technique using 3 × 3 and 5 × 5 masks separately of which better one in terms of fitness is chosen. The detection method is based on all neighbour directional pixels. The filtering method is based on weighted median approach. Out of the three user parameters used for detection and filtering, a single one is searched in a wide range using PSO to obtain the optimal solutions. The results obtained demonstrate the effectiveness of the proposed technique. On both the noise models same type of results and comparisons have been carried out and time requirement for the techniques have also been studied and compared.

Keywords: all neighbour directional pixels; weighted median filter; image denoising; particle swarm optimisation; PSO; random valued noise; RVN; salt and pepper noise; SPN; sub-image restoration; threshold optimisation; digital images; image processing; impulse filtering.

DOI: 10.1504/IJCISTUDIES.2015.072874

International Journal of Computational Intelligence Studies, 2015 Vol.4 No.3/4, pp.288 - 312

Received: 29 Jan 2014
Accepted: 22 Nov 2014
Published online: 05 Nov 2015 *

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