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International Conference on Information Processing

ICIP 2012: Wireless Networks and Computational Intelligence pp 220–229Cite as

Capsule Endoscopic Colour Image Denoising Using Complex Wavelet Transform

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 292))

Abstract

In this paper, wavelet transform based capsule endoscopic colour image denoising method is proposed. Recent research in image denoising methods mainly focused on wavelet transform as its superior performance over other transforms. In this proposed method double density dual tree complex wavelet transform (DDDT-ℂWT) is used due to its ability to implement as complex and multi-directional wavelet transform. Denoising is done in YCbCr colour space, which provides good results in terms of peak signal to noise ratio (PSNR) and structural similarity (SSIM) than RGB colour space.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology (NIT), Tiruchirappalli, Tamilnadu, 620015, India

    Varun P. Gopi, P. Palanisamy & S. Issac Niwas

Authors
  1. Varun P. Gopi
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  2. P. Palanisamy
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  3. S. Issac Niwas
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, 560 001, Bangalore, India

    K. R. Venugopal

  2. Indian Institute of Science, Bangalore, India

    L. M. Patnaik

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© 2012 Springer-Verlag Berlin Heidelberg

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Gopi, V.P., Palanisamy, P., Niwas, S.I. (2012). Capsule Endoscopic Colour Image Denoising Using Complex Wavelet Transform. In: Venugopal, K.R., Patnaik, L.M. (eds) Wireless Networks and Computational Intelligence. ICIP 2012. Communications in Computer and Information Science, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31686-9_26

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  • DOI: https://doi.org/10.1007/978-3-642-31686-9_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31685-2

  • Online ISBN: 978-3-642-31686-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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