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Soft Computing

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16.12.2014 | Methodologies and Application

Adaptive image denoising using cuckoo algorithm

verfasst von: Memoona Malik, Faraz Ahsan, Sajjad Mohsin

Erschienen in: Soft Computing | Ausgabe 3/2016

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Abstract

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.

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Titel: Adaptive image denoising using cuckoo algorithm
verfasst von: Memoona Malik
Faraz Ahsan
Sajjad Mohsin
Publikationsdatum: 16.12.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 3/2016
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1552-x

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