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Estimation and optimization based ill-posed inverse restoration using fuzzy logic

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Abstract

Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods.

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Acknowledgements

The authors would like to acknowledge Higher Education Commission (HEC) of Pakistan for their continuous financial support and the reviewers for their many valuable comments and suggestions that helped to improve this paper.

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Authors and Affiliations

  1. National University of Computer and Emerging Sciences, H-11/4, Islamabad, Pakistan

    Mohsin Bilal & Muhammad Arfan Jaffar

  2. International Islamic University, H-12, Islamabad, Pakistan

    Ayyaz Hussain

  3. Gwangju Institute of Science and Technology, Gwangju, Korea

    Tae-Sun Choi

  4. King Saud University, Riyadh, Saudi Arabia

    Anwar M. Mirza

Authors
  1. Mohsin Bilal
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  2. Ayyaz Hussain
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  3. Muhammad Arfan Jaffar
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  4. Tae-Sun Choi
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  5. Anwar M. Mirza
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Corresponding author

Correspondence to Muhammad Arfan Jaffar.

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Bilal, M., Hussain, A., Jaffar, M.A. et al. Estimation and optimization based ill-posed inverse restoration using fuzzy logic. Multimed Tools Appl 69, 1067–1087 (2014). https://doi.org/10.1007/s11042-012-1172-3

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