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Color Image Restoration with Fuzzy Gaussian Mixture Model Driven Nonlocal Filter

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Analysis of Images, Social Networks and Texts (AIST 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 542))

Abstract

Color image denoising is one of the classical image processing problem and various techniques have been explored over the years. Recently, nonlocal means (NLM) filter is proven to obtain good results for denoising Gaussian noise corrupted digital images using weighted mean among similar patches. In this paper, we consider fuzzy Gaussian mixture model (GMM) based NLM method for removing mixed Gaussian and impulse noise. By computing an automatic homogeneity map we identify impulse noise locations and utilize an adaptive patch size. Experimental results on mixed noise affected color images show that our scheme performs better than NLM, anisotropic diffusion and GMM-NLM over different noise levels. Comparison with respect to structural similarity, color image difference, and peak signal to noise ratio error metrics are undertaken and our scheme performs well overall without generating color artifacts.

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Notes

  1. 1.

    Color image converted using MATLAB’s rgb2gray which uses the following formula \(I_g = 0.2989 * R + 0.5870 * G + 0.1140 * B\), where R, G, B are the red, green, and blue channels of the given color image. Images are normalized to [0, 1].

  2. 2.

    For a non-diagonal symmetric matrix \(\varSigma \) there exists orthogonal matrix \(\mathcal {O}\) and diagonal matrix \(\varLambda \) such that \(\varSigma ^{-1} = \mathcal {O}\varLambda \mathcal {O}\).

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Acknowledgments

This work was done while the first author was visiting the Center for Scientific Computation and Mathematical Modeling (CSCAMM), University of Maryland, College Park, MD, USA in the summer of 2014. The first author thanks the CSCAMM institute for their great hospitality and support during the visit.

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Authors and Affiliations

  1. University of Missouri-Columbia, Columbia, MO, 65211, USA

    V. B. Surya Prasath

  2. Knowledge Based System Group, Higher Institute for Information Technology and Information Systems, Kazan Federal University, Kazan, Russia

    Radhakrishnan Delhibabu

Authors
  1. V. B. Surya Prasath
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  2. Radhakrishnan Delhibabu
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Corresponding author

Correspondence to V. B. Surya Prasath .

Editor information

Editors and Affiliations

  1. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Mikhail Yu. Khachay

  2. Wolverhampton, United Kingdom

    Natalia Konstantinova

  3. Technische Universität Darmstadt, Darmstadt, Germany

    Alexander Panchenko

  4. National Research University Higher School of Economics, Moscow, Russia

    Dmitry Ignatov

  5. Ural Federal University, Yekaterinbug, Russia

    Valeri G. Labunets

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Surya Prasath, V.B., Delhibabu, R. (2015). Color Image Restoration with Fuzzy Gaussian Mixture Model Driven Nonlocal Filter. In: Khachay, M., Konstantinova, N., Panchenko, A., Ignatov, D., Labunets, V. (eds) Analysis of Images, Social Networks and Texts. AIST 2015. Communications in Computer and Information Science, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-319-26123-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-26123-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26122-5

  • Online ISBN: 978-3-319-26123-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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