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Vector Median M-Type L Filter to Process Multichannel Images

  • Antonio Toledo-Lopez
  • Francisco J. Gallegos-Funes
  • Volodymyr Ponomaryov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)

Abstract

The Vector Median M-type L (VMML) -filter to remove impulsive noise from color images and video color sequences is presented. This filter utilizes multichannel image processing by using the vector approach and the Median M-Type L (MML) algorithm. Simulation results indicate that the proposed filter consistently outperforms other color image filters by balancing the tradeoff between noise suppression, detail preservation, and color retention.

Keywords

Median M-Type L algorithm Multichannel image processing Impulsive noise suppression 

References

  1. 1.
    Bovik, A.: Handbook of Image and Video Processing. Academic Press, San Diego (2000)zbMATHGoogle Scholar
  2. 2.
    Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Berlin (2000)CrossRefGoogle Scholar
  3. 3.
    Astola, J., Kuosmanen, P.: Fundamentals of Nonlinear Digital Filtering. CRC Press, Boca Raton (1997)zbMATHGoogle Scholar
  4. 4.
    Plataniotis, K.N., Androutsos, D., Vinayagamoorthy, S., Venetsanopoulos, A.N.: Color image processing using adaptive multichannel filters. IEEE Trans. Image Process 6–7, 933–949 (1997)Google Scholar
  5. 5.
    Varela-Benitez, J.L., Gallegos-Funes, F.J., Ponomaryov, V.: RM L-filters for Real Time Imaging. In: IEEE 15th International Conference on Computing, pp. 43–48. IEEE Press, Mexico City (2006)Google Scholar
  6. 6.
    Varela-Benítez, J.L., Gallegos-Funes, F.J., Ponomaryov, V.I.: Real-time speckle and impulsive noise suppression in 3-D imaging based on robust linear combinations of order statistics. In: SPIE 6496 Real-Time Image Processing 2007, p. 64960H. SPIE Press, San Jose (2007)CrossRefGoogle Scholar
  7. 7.
    Gallegos-Funes, F.J., Ponomaryov, V.I.: Real-time image filtering scheme based on robust estimators in presence of impulsive noise. Real Time Imaging 10(2), 69–80 (2004)CrossRefGoogle Scholar
  8. 8.
    Pitas, I., Venetsanopoulos, A.N.: Nonlinear Digital Filters. Kluwer Academic Publishers, Boston (1990)CrossRefzbMATHGoogle Scholar
  9. 9.
    Aizenberg, I., Astola, J., Bregin, T., Butakoff, C., Egiazarian, K., Paily, D.: Detectors of the impulsive noise and new effective filters for the impulsive noise reduction. In: SPIE 5014 Image Processing, Algorithms and Systems II, pp. 419–428. SPIE Press (2003)Google Scholar
  10. 10.
    Trahanias, P.E., Karakos, D.G., Venetsanopoulos, A.N.: Directional processing of color images: Theory and experimental results. IEEE Trans. Image Process. 5, 868–880 (1996)CrossRefGoogle Scholar
  11. 11.
    Ponomaryov, V., Gallegos-Funes, F., Rosales-Silva, A.: Real-Time Color Image Processing Using Order Statistics Filters. Journal of Mathematical Imaging and Vision 23(3), 315–319 (2005)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Smolka, B., Lukac, R., Chydzinski, A., Plataniotis, K.N., Wojciechowski, W.: Fast adaptive similarity based impulsive noise reduction filter. Real-Time Imaging, 261–276 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Antonio Toledo-Lopez
    • 1
  • Francisco J. Gallegos-Funes
    • 1
  • Volodymyr Ponomaryov
    • 1
  1. 1.National Polytechnic Institute of Mexico, Mechanical and Electrical Engineering Higher School, UPALM ZacatencoMexico D.F.Mexico

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