Image denoising using generalised Cauchy filter

Karami, A and Tafakori, L 2017, 'Image denoising using generalised Cauchy filter', IET Image Processing, vol. 11, no. 9, pp. 767-776.


Document type: Journal Article
Collection: Journal Articles

Title Image denoising using generalised Cauchy filter
Author(s) Karami, A
Tafakori, L
Year 2017
Journal name IET Image Processing
Volume number 11
Issue number 9
Start page 767
End page 776
Total pages 10
Publisher Institution of Engineering and Technology
Abstract In many image processing analysis, it is important to significantly reduce the noise level. This study aims at introducing an efficient method for this purpose based on generalised Cauchy (GC) distribution. Therefore, some characteristics of GC distribution is considered. In particular, the characteristic function of a GC distribution is derived by using the theory of positive definite densities and utilising the density of a GC random variable as the characteristic function of a convolution of two generalised non-symmetric Linnik variables. Further, GC distribution is considered as a filter and in the proposed method for image noise reduction the optimal parameters of GC filter is defined by using the particle swarm optimisation. The proposed method is applied to different types of noisy images and the obtained results are compared with four state-of-the-art denoising algorithms. Experimental results confirm that their method could significantly reduce the noise effect.
Subject Probability Theory
Applied Statistics
Statistical Theory
DOI - identifier 10.1049/iet-ipr.2016.0554
Copyright notice © The Institution of Engineering and Technology 2017
ISSN 1751-9659
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