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Soft Computing

, Volume 20, Issue 3, pp 925–938 | Cite as

Adaptive image denoising using cuckoo algorithm

  • Memoona Malik
  • Faraz Ahsan
  • Sajjad Mohsin
Methodologies and Application

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.

Keywords

Image denoising Smoothing filters Cuckoo search Gaussian noise Speckle noise Salt and pepper noise 

Abbreviations

AI

Artificial intelligence

CSA

Cuckoo search algorithm

db4

Daubechies-4 wavelet

IQI

Image quality index

GA

Genetic algorithms

PSO

Particle swarm optimization

PSNR

Peak signal-to-noise ratio

SNR

Signal-to-noise ratio

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Comsats Institute of Information TechnologyIslamabadPakistan
  2. 2.PMAS-UIITRawalpindiPakistan

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