OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Stephen A. Burns
  • Vol. 26, Iss. 6 — Jun. 1, 2009
  • pp: 1518–1524

Cost-effective implementation of order-statistics-based vector filters using minimax approximations

M. Emre Celebi, Hassan A. Kingravi, Rastislav Lukac, and Fatih Celiker  »View Author Affiliations


JOSA A, Vol. 26, Issue 6, pp. 1518-1524 (2009)
http://dx.doi.org/10.1364/JOSAA.26.001518


View Full Text Article

Enhanced HTML    Acrobat PDF (676 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Vector operators based on robust order statistics have proved successful in digital multichannel imaging applications, particularly color image filtering and enhancement, in dealing with impulsive noise while preserving edges and fine image details. These operators often have very high computational requirements, which limits their use in time-critical applications. This paper introduces techniques to speed up vector filters using the minimax approximation theory. Extensive experiments on a large and diverse set of color images show that proposed approximations achieve an excellent balance among ease of implementation, accuracy, and computational speed.

© 2009 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2980) Image processing : Image enhancement
(100.3010) Image processing : Image reconstruction techniques

ToC Category:
Image Processing

History
Original Manuscript: January 21, 2009
Manuscript Accepted: March 25, 2009
Published: May 29, 2009

Citation
M. Emre Celebi, Hassan A. Kingravi, Rastislav Lukac, and Fatih Celiker, "Cost-effective implementation of order-statistics-based vector filters using minimax approximations," J. Opt. Soc. Am. A 26, 1518-1524 (2009)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-26-6-1518


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. K. N. Plataniotis and A. N. Venetsanopoulos, Color Image Processing and Applications (Springer, 2000).
  2. R. Lukac and K. N. Plataniotis, “A taxonomy of color image filtering and enhancement solutions,” in Advances in Imaging & Electron Physics, P.W.Hawkes, ed. (Academic, 2006), (Vol. 140), pp. 187-264. [CrossRef]
  3. M. E. Celebi, H. A. Kingravi, and Y. A. Aslandogan, “Nonlinear vector filtering for impulsive noise removal from color images,” J. Electron. Imaging 16, 033008 (2007). [CrossRef]
  4. R. Lukac, B. Smolka, K. Martin, K. N. Plataniotis, and A. N. Venetsanopoulos, “Vector filtering for color imaging,” IEEE Signal Process. Mag. 22, 74-86 (2005). [CrossRef]
  5. M. E. Celebi and Y. A. Aslandogan, “Robust switching vector median filter for impulsive noise removal,” J. Electron. Imaging 17, 043006 (2008). [CrossRef]
  6. M. Barni, “A fast algorithm for 1-norm vector median filtering,” IEEE Trans. Image Process. 6, 1452-1455 (1997). [CrossRef] [PubMed]
  7. M. Barni, F. Buti, F. Bartolini, and V. Cappellini, “A quasi-Euclidean norm to speed up vector median filtering,” IEEE Trans. Image Process. 9, 1704-1709 (2000). [CrossRef]
  8. J. Astola, P. Haavisto, and Y. Neuvo, “Vector median filters,” Proc. IEEE 78, 678-689 (1990). [CrossRef]
  9. M. E. Celebi, H. A. Kingravi, B. Uddin, and Y. A. Aslandogan, “Fast switching filter for impulsive noise removal from color images,” J. Imaging Sci. Technol. 51, 155-165 (2007). [CrossRef]
  10. P. E. Trahanias and A. N. Venetsanopoulos, “Vector directional filters: A new class of multichannel image processing filters,” IEEE Trans. Image Process. 2, 528-534 (1993). [CrossRef] [PubMed]
  11. K. N. Plataniotis, D. Androutsos, S. Vinayagamoorthy, and A. N. Venetsanopoulos, “Color image processing using adaptive multichannel filters,” IEEE Trans. Image Process. 6, 933-949 (1997). [CrossRef] [PubMed]
  12. R. Lukac, B. Smolka, K. N. Plataniotis, and A. N. Venetsanopoulos, “Entropy vector median filter,” in Proceedings of the IbPRIA Conference, Lecture Notes in Computer Science 2652 (Springer, 2003), pp. 1117-1125.
  13. E. W. Cheney, Introduction to Approximation Theory (AMS, 2000).
  14. J.-M. Muller, Elementary Functions: Algorithms and Implementation (Birkhäuser, 2006).
  15. W. Fraser, “A survey of methods of computing minimax and near-minimax polynomial approximations for functions of a single independent variable,” J. ACM 12, 295-314 (1965). [CrossRef]
  16. N. Nikolaidis and I. Pitas, “Nonlinear processing and analysis of angular signals,” IEEE Trans. Signal Process. 46, 3181-3194 (1998). [CrossRef]
  17. P. E. Trahanias, D. Karakos, and A. N. Venetsanopoulos, “Directional processing of color images: Theory and experimental results,” IEEE Trans. Image Process. 5, 868-880 (1996). [CrossRef] [PubMed]
  18. D. G. Karakos and P. E. Trahanias, “Generalized multichannel image filtering structures,” IEEE Trans. Image Process. 6, 1038-1045 (1997). [CrossRef] [PubMed]
  19. L. Khriji and M. Gabbouj, “Adaptive fuzzy order statistics-rational hybrid filters for color image processing,” Fuzzy Sets Syst. 128, 35-46 (2002). [CrossRef]
  20. R. Lukac, “Adaptive color image filtering based on center-weighted vector directional filters,” Multidimens. Syst. Signal Process. 15, 169-196 (2004). [CrossRef]
  21. K. N. Plataniotis, D. Androutsos, and A. N. Venetsanopoulos, “Color image processing using adaptive vector directional filters,” IEEE Trans. on Circuits and Systems-II 45, 1414-1419 (1998). [CrossRef]
  22. R. Lukac, B. Smolka, K. N. Plataniotis, and A. N. Venetsanopoulos, “Vector sigma filters for noise detection and removal in color images,” J. Visual Commun. Image Represent 17, 1-26 (2006). [CrossRef]
  23. K. N. Plataniotis, D. Androutsos, and A. N. Venetsanopoulos, “Adaptive fuzzy systems for multichannel signal processing,” Proc. IEEE 87, 1601-1622 (1999). [CrossRef]
  24. B. Smolka, K. N. Plataniotis, R. Lukac, and A. N. Venetsanopoulos, “Kernel density estimation based impulsive noise reduction filter,” in Proceedings of the IEEE International Conference on Image Processing (ICIP'03) (IEEE, 2003), Vol. 2, pp. 137-140.
  25. B. Smolka, R. Lukac, A. Chydzinski, K. N. Plataniotis, and K. Wojciechowski, “Fast adaptive similarity based impulsive noise reduction filter,” Real-Time Imag. 9, 261-276 (2003). [CrossRef]
  26. B. Smolka, K. N. Plataniotis, A. Chydzinski, M. Szczepanski, A. N. Venetsanopoulos, and K. Wojciechowski, “Self-adaptive algorithm of impulsive noise reduction in color images,” Pattern Recogn. 35, 1771-1784 (2002). [CrossRef]
  27. R. Lukac, B. Smolka, K. N. Plataniotis, and A. N. Venetsanopoulos, “Generalized entropy vector filters,” in Proceedings of the 4th EURASIP EC-VIP-MC, Video, Image Processing and Multimedia Communications Conference (IEEE, 2003), pp. 239-244.
  28. T. Viero, K. Oistamo, and Y. Neuvo, “Three-dimensional median-related filters for color image sequence filtering,” IEEE Trans. Circuits Syst. Video Technol. 4, 129-142 (1994). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article

OSA is a member of CrossRef.

CrossCheck Deposited