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A Denoising Approach for Salt and Pepper Noise Corrupted Image at Higher Noise Density

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Advances in Digital Image Processing and Information Technology (DPPR 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 205))

Abstract

Image restoration and noise reduction is an eminent problem in almost all image processing applications. Numerous image restoration methods have been developed, each of which has its own advantages and limitation. This paper proposes a novel approach for removal of salt and pepper noise using a two stage process, in which the noisy image is first subjected to an adaptive median filter and then its output is further denoised by applying it to a new patch based non- local recovery paradigm. The Non-Local means filter uses the redundancy of information in the image under study to remove the noise. The statistical results of simulations are done using MATLAB and the obtained denoised images are quantified using various performance metrics.

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References

  1. Chan, R.H., Ho, C.-W., Nikolova, M.: Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization. IEEE Transactions on Image Processing 14(10) (October 2005)

    Google Scholar 

  2. Astola, J., Kuosmanen, P.: Fundamentals of Nonlinear Digital Filtering. CRC, Boca Raton (1997)

    MATH  Google Scholar 

  3. Chen, T., Whu, H.R.: Space Space variant median filters for the restoration of impulse noise corrupted images. IEEE Trans. Image Processing 7, 784–789 (1998)

    Google Scholar 

  4. Hwang, H., Haddad, R.A.: Adaptive median filters: new algorithms and results. IEEE Transactions on Image Processing 4, 499–502 (1995)

    Article  Google Scholar 

  5. Jayaraj, V., Ebenezer, D., Aiswarya, K.: High Density Salt and Pepper Noise Removal in images using Improved Adaptive Statistics Estimation Filter. IJCSNS International Journal of Computer Science an 170 d Network Security 9(11) (November 2009)

    Google Scholar 

  6. Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing Using MATLAB. Prentice-Hall, Englewood Cliffs (2004)

    Google Scholar 

  7. Buades, A., Coll, B., Morel, J.M.: A review of image denoising algorithms with a new one. Society for Industrial and Applied Mathematics 4(2), 490–530 (2005)

    MathSciNet  MATH  Google Scholar 

  8. Buades, A., Coll, B., Morel, J.M.: A non local algorithm for image denoising. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 60–65 (2005)

    Google Scholar 

  9. Ko, S.-J., Lee, Y.H.: Center weighted median filters and their applications to image enhancement. IEEE Trans. Circuits Syst. 38(9), 984–993 (1991)

    Article  Google Scholar 

  10. Sun, T., Neuvo, Y.: Detail-preserving median based filters in image processing. Pattern Recognit. Lett. 15(4), 341–347 (1994)

    Article  Google Scholar 

  11. Maragos, P., Schafer, R.: Morphological Filters–Part II: Their Relations to Median, Order-Statistic, and Stack Filters. IEEE Trans. Acoust., Speech, Signal Processing 35(8), 1170–1184 (1987)

    Article  MathSciNet  Google Scholar 

  12. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice-Hall, Englewood Cliffs (2002)

    Google Scholar 

  13. Vijaykumar, V.R., Vanathi, P.T., Kanagasabapathy, P., Ebenezer, D.: Robust Statistics Based Algorithm to Remove Salt and Pepper Noise in Images. International Journal of Information and Communication Engineering 5, 3 (2009)

    Google Scholar 

  14. Juneja, M., Sandhu, P.S.: Design and Development of an Improved Adaptive Median Filtering Method for Impulse Noise Detection. International Journal of Computer and Electrical Engineering 1(5) (December 2009)

    Google Scholar 

  15. Sarker, S., Devi, S.: Effect of Non-Local Means filter in a Homomorphic Framework Cascaded with Bacterial Foraging Optimization to Eliminate Speckle. CiiT International Journal of Digital Image Processing 3(2) (February 2011)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics & Communication Engineering, Siliguri Institute Of Technology, Sukna, Darjeeling, India

    Debika Dey, Samanwita Laha, Shalini Chowdhury & Subhojit Sarker

Authors
  1. Debika Dey
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  2. Samanwita Laha
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  3. Shalini Chowdhury
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  4. Subhojit Sarker
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Editor information

Editors and Affiliations

  1. Wireilla Net Solutions PTY Ltd, Melbourne, Victoria, Australia

    Dhinaharan Nagamalai

  2. Institut Telecom/Telecom SudParis, 9, rue Charles Fourier, 91011, Evry Cedex, France

    Eric Renault

  3. Manonmaniam Sundaranar University, Thirunelveli, Tamil Nadu, India

    Murugan Dhanuskodi

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© 2011 Springer-Verlag Berlin Heidelberg

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Dey, D., Laha, S., Chowdhury, S., Sarker, S. (2011). A Denoising Approach for Salt and Pepper Noise Corrupted Image at Higher Noise Density. In: Nagamalai, D., Renault, E., Dhanuskodi, M. (eds) Advances in Digital Image Processing and Information Technology. DPPR 2011. Communications in Computer and Information Science, vol 205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24055-3_18

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  • DOI: https://doi.org/10.1007/978-3-642-24055-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24054-6

  • Online ISBN: 978-3-642-24055-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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