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PSO Based Blind Deconvolution Technique of Image Restoration Using Cepstrum Domain of Motion Blur

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Book cover Computational Vision and Bio Inspired Computing

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 28))

Abstract

In this paper, blind deconvolution technique is planned based on the Particle Swarm Optimization (PSO) and cepstrum method. Angle and distance is obtained from motion blurred images using cepstrum method. The parameters of cepstrum are optimized through PSO technique. Here, we are optimizing values of theta and length from cepstrum of blurred image, which will help in PSF calculations. To extend the result of our previous work (Almeida and Almeidain in IEEE Trans Image Process 19(1):36–52, 2010 [1]) we have used PSO technique which is giving better result than GA. Also the convergence rate is faster and computational time of an algorithm is also reduced. Hence, the proposed method outperforms the previous method.

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Authors and Affiliations

  1. Chandigarh Engineering College, Chandigarh, India

    G. Ramteke Mamta

  2. Department of Computer Science and Engineering, NITTTR, Chandigarh, India

    Maitreyee Dutta

Authors
  1. G. Ramteke Mamta
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  2. Maitreyee Dutta
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Correspondence to Maitreyee Dutta .

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Editors and Affiliations

  1. Karunya University , Coimbatore, Tamil Nadu, India

    D. Jude Hemanth

  2. RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

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Ramteke Mamta, G., Dutta, M. (2018). PSO Based Blind Deconvolution Technique of Image Restoration Using Cepstrum Domain of Motion Blur. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_81

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  • DOI: https://doi.org/10.1007/978-3-319-71767-8_81

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71766-1

  • Online ISBN: 978-3-319-71767-8

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