Skip to main content
SpringerLink
Log in

Monochromatic-Based Method for Impulse Noise Detection and Suppression in Color Images

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. J. Astola, P. Haavisto, Y. Neuvo, Vector median filters. IEEE Proc. 78(4), 678–689 (1990)

    Article  Google Scholar 

  2. A. Brook, R. Kimmel, N. Sochen, Variational restoration and edge detection for color images. J. Math. Imaging Vis. 18, 247–268 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  3. N. Galatsanos, M. Wernick, A. Katsaggelos, R. Molina, Multichannel image recovery, in Handbook of Image and Video Processing, ed. by A. Bovik (Academic Press, New York, 2005), pp. 203–218

    Chapter  Google Scholar 

  4. E. Hore, B. Qiu, H. Wu, Improved vector filtering for color images using fuzzy noise detection. Opt. Eng. 42(6), 1656–1664 (2003)

    Article  Google Scholar 

  5. A. Koschan, M. Abidi, Digital Color Image Processing (Wiley, Hoboken, 2008)

    Book  Google Scholar 

  6. S. Kwanghoon, L. Kyu-Cheol, L. Jungeun, Impulsive noise filtering based on noise detection in corrupted digital color images. Circuits Syst. Signal Process. 20(6), 643–654 (2001)

    Article  MATH  Google Scholar 

  7. J. Lianghai, L. Dehua, An efficient color-impulse detector and its application to color images. IEEE Signal Process. Lett. 14(6), 397–400 (2007)

    Article  Google Scholar 

  8. J. Lianghai, L. Hong, X. Xiangyang, S. Enmin, Quaternion-based color image filtering for impulsive noise suppression. J. Electron. Imaging 19, 043003 (2010)

    Article  Google Scholar 

  9. R. Lukac, Adaptive vector median filtering. Pattern Recognit. Lett. 24(12), 1889–1899 (2003)

    Article  Google Scholar 

  10. R. Lukac, Adaptive color image filtering based on center-weighted vector directional filter. Multidimens. Syst. Signal Process. 15, 169–196 (2004)

    Article  MATH  Google Scholar 

  11. R. Lukac, K. Plataniotis, A. Venetsanopoulos, B. Smolka, A statistically-switched adaptive vector median filter. J. Intell. Robot. Syst. 42(4), 361–391 (2005)

    Article  Google Scholar 

  12. R. Lukac, B. Smolka, K. Plataniotis, Sharpening vector median filters. Signal Process. 87, 2085–2099 (2007)

    Article  MATH  Google Scholar 

  13. R. Lukac, B. Smolka, K. Martin, K. Plataniotis, A. Venetsanopoulos, Vector filtering for color imaging. IEEE Signal Process. Mag. 22(1), 74–86 (2005)

    Article  Google Scholar 

  14. R. Lukac, B. Smolka, K. Plataniotis, A. Venetsanopoulos, Generalized adaptive vector sigma filters, in Proc. of IEEE International Conference on Multimedia and Expo (ICME), vol. 1, Baltimore, MD, USA (2003), pp. 537–540

    Google Scholar 

  15. R. Lukac, B. Smolka, K. Plataniotis, A. Venetsanopoulos, Vector sigma filters for noise detection and removal in color images. J. Vis. Commun. Image Represent. 17(1), 1–26 (2006)

    Article  Google Scholar 

  16. R. Lukac, Color image filtering by vector directional order statistics. Pattern Recognit. Image Anal. 12(3), 279–285 (2002)

    MathSciNet  Google Scholar 

  17. Z. Ma, H. Wu, B. Qiu, A robust structure-adaptive hybrid vector filter for color image restoration. IEEE Trans. Image Process. 14(12), 1990–2001 (2005)

    Article  Google Scholar 

  18. T. Mélange, M. Nachtegael, E. Kerre, Fuzzy random impulse noise removal from color image sequences. IEEE Trans. Image Process. 20(4), 959–970 (2011)

    Article  MathSciNet  Google Scholar 

  19. S. Morillas, V. Gregori, G. Peris-Fajarnes, P. Latorre, A fast impulsive noise color image filter using fuzzy metrics. Real-Time Imaging 11(5–6), 417–428 (2005)

    Article  Google Scholar 

  20. K. Plataniotis, A. Venetsanopoulos, Color Image Processing and Applications (Springer, Berlin, 2000)

    Book  Google Scholar 

  21. S. Schulte, V. Witte, M. Nachtegael, D. Weken, E. Kerre, Fuzzy two-step filter for impulse noise reduction from color images. IEEE Trans. Image Process. 15(11), 3567–3578 (2006)

    Article  Google Scholar 

  22. Y. Shen, K. Barner, Fast adaptive optimization of weighted vector median filters. IEEE Trans. Signal Process. 54(7), 2497–2510 (2006)

    Article  Google Scholar 

  23. B. Smolka, Efficient modification of the central weighted vector median filter. Lect. Notes Comput. Sci. 2449, 166–173 (2002)

    Article  Google Scholar 

  24. B. Smolka, A. Chydzinski, Fast detection and impulsive noise removal in color images. Real-Time Imaging 11(5–6), 389–402 (2005)

    Article  Google Scholar 

  25. B. Smolka, K. Plataniotis, A. Chydzinski, M. Szczepanski, A. Venetsanopoulos, K. Wojciechowski, Self-adaptive algorithm of impulsive noise reduction in color images. Pattern Recognit. 35(8), 1771–1784 (2002)

    Article  MATH  Google Scholar 

  26. Z. Wang, A. Bovik, H. Sheikh, E. Simoncelli, Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Zayed M. Ramadan

Authors
  1. Zayed M. Ramadan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zayed M. Ramadan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ramadan, Z.M. Monochromatic-Based Method for Impulse Noise Detection and Suppression in Color Images. Circuits Syst Signal Process 32, 1859–1874 (2013). https://doi.org/10.1007/s00034-012-9547-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-012-9547-2

Keywords

Search

Navigation