Skip to main content

Detection and Reduction of Impulse Noise in RGB Color Image Using Fuzzy Technique

  • Conference paper
Distributed Computing and Internet Technology (ICDCIT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8337))

Abstract

A concept of impulse noise reduction method for an RGB color image with a fuzzy detection phase is introduced and a fuzzy de-noising procedure is used to filter the color image. In this paper, each color component is correlated to the other two corresponding color components to overcome the color disorder on edge and texture pixel. Here the filtering technique is only applied to noisy pixel, detected by fuzzy technique, while preserving the color and edge sharpness. Experimental results show that the proposed method provides noteworthy improvement on other non-fuzzy and fuzzy filters.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Xu, H., Zhu, G., Peng, H., Wang, D.: Adaptive fuzzy switching filter for images corrupted by impulse noise. Pattern Recognit. Lett. 25, 1657–1663 (2004)

    Article  Google Scholar 

  2. Nachtegael, M., Van der Weken, D., De Witte, V., Schulte, S., Melange, T., Kerre, E.E.: Color Image retrieval fuzzy similarity measures and fuzzy partitions. In: IEEE, ICIP, vol. VI (2007)

    Google Scholar 

  3. Schulte, S., Nachtegael, M., De Witte, V., Van der Weken, D., Kerre, E.E.: A fuzzy impulse noise detection and reduction method. IEEE Tans. Image Process. 15(5), 1153–1162 (2006)

    Article  Google Scholar 

  4. Wang, J.H., Liu, W.J., Lin, L.D.: Histogram-Based fuzzy filter for image restoration. IEEE Trans. Syst., Man, Cybern. B, Cybern. 32(2), 230–238 (2002)

    Article  MathSciNet  Google Scholar 

  5. Kalaykov, L., Tolt, G.: Real-time image noise cancellation based on fuzzy similarity. In: Nachtegael, M., Van der Weken, D., Van De Ville, D., Kerre, E.E. (eds.) Fuzzy Filters for Image Processing, 1st edn., vol. 122, pp. 54–71. Physica Verlag, Heidelberg (2003)

    Chapter  Google Scholar 

  6. Schulte, S., Morillas, S., Gregori, V., Kerre, E.E.: A New fuzzy color correlated impulse noise reduction method. IEEE Trans. on Image Processing 16(10) (October 2007)

    Google Scholar 

  7. Schulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Fuzzy random impulse noise reduction method. Fuzzy Sets Syst. 158(3), 270–283 (2007)

    Article  Google Scholar 

  8. Schulte, S., Witte, V.D., Nachtegael, M., Weken, D.V.: Fuzzy Two-step Filter for Impulse Noise Reduction from Color Image. IEEE Trans. Image Processing 15(11), 3567–3578 (2006)

    Article  Google Scholar 

  9. Rao, G.V., Somayajula, S.P.K., Mohan Rao, C.P.V.N.J.: Implementation of Impulse noise reduction method to color images using fuzzy logic. Global Journal of Computer Science and Technology 11(22), 72–75 (2011)

    Google Scholar 

  10. Plataniotis, K.N., Venetsanopouls, A.N.: Color image processing and Applications. Springer, Berlin (2000)

    Book  Google Scholar 

  11. Lukac, R.: Adaptive vector median filter. Pattern Recognit. Lett. 24(12), 1889–1899 (2003)

    Article  Google Scholar 

  12. Barni, M., Cappellini, V., Mecocci, A.: Fast Vector median filter based on Euclidean norm approximate. IEEE Signal Process. Lett. 1(6), 92–94 (1994)

    Article  Google Scholar 

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

    Article  Google Scholar 

  14. Sűsstrunk, S., Buckley, R., Swen, S.: Standard RGB Color space, Laboratory of Audio-visual Comm(EPFL), Xerox Architecture Center, Apple Computer Lausanne, Switzerland, Vebster

    Google Scholar 

  15. Morillas, S., Schulte, S., Kerre, E.E., Peris-Fajarnés, G.: A New Fuzzy Impulse Noise Detection Method for Colour Images. In: Ersbøll, B.K., Pedersen, K.S. (eds.) SCIA 2007. LNCS, vol. 4522, pp. 492–501. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  16. Jang, J.-S.R., Sun, C.-T., Mizutani, E.: Neuro-Fuzzy and Soft Computing. PHI Learning Pvt., Ltd.

    Google Scholar 

  17. Nachbar, J.: Basic properties of Euclidean Norm. Economics 511 (2009)

    Google Scholar 

  18. Suapang, P., Dejhan, K., Yimmun, S.: Medical Image Processing and Analysis for Nuclear Medicine Diagnosis. In: International Conference on Control, Automation and Systems, KINTEX, Gyeonggi-do, Korea, October 27-30 (2010)

    Google Scholar 

  19. Laban, N., Nasr, A., ElSaban, M., Onsi, H.: Spatial Cloud Detection and Retrieval System for Satellite Images. International Journal of Advanced Computer Science and Applications 3(12) (2012)

    Google Scholar 

  20. Allen, M.P., Graham, E., Ahamadian, S., Ko, T., Yuen, E., Girod, L., Hamilton, M., Estrin, D.: Interactive Environmental Sensing: Signal and Image processing Challenges, Center for Embedded Network Sensing, University of California, Los Angeles

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Mishra, D., Bose, I., Das, M., Mishra, B.S.P. (2014). Detection and Reduction of Impulse Noise in RGB Color Image Using Fuzzy Technique. In: Natarajan, R. (eds) Distributed Computing and Internet Technology. ICDCIT 2014. Lecture Notes in Computer Science, vol 8337. Springer, Cham. https://doi.org/10.1007/978-3-319-04483-5_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-04483-5_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-04482-8

  • Online ISBN: 978-3-319-04483-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics