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


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.


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



Artificial intelligence


Cuckoo search algorithm


Daubechies-4 wavelet


Image quality index


Genetic algorithms


Particle swarm optimization


Peak signal-to-noise ratio


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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