Localised rank-ordered differences vector filter for suppression of high-density impulse noise in colour images

Bernardino Roig; Vicente D. Estruch

Localised rank-ordered differences vector filter for suppression of high-density impulse noise in colour images

View Fulltext

Author(s): Bernardino Roig ¹ and Vicente D. Estruch ¹
- Affiliations: 1: Universidad Politécnica de Valencia, E.P.S. Gandia, C/Paranimf, 1., 46730 Grau de Gandia (Valencia), Spain
Source: Volume 10, Issue 1, January 2016, p. 24 – 33
DOI: 10.1049/iet-ipr.2014.0838 , Print ISSN 1751-9659, Online ISSN 1751-9667

Received 21/10/2014, Accepted 05/07/2015, Revised 09/06/2015, Published 01/01/2016

This research presents a complete study of a new alternating vector filter for the removal of impulsive noise in colour images. The method is based on an impulsive noise detector for greyscale images that has been adapted in a localised manner using geometric information for processing colour images. Based on this statistic, a filtering scheme alternating between the identity and a non-linear vector filter is proposed. A geometric and experimental study was performed to obtain the optimal filter design. Experimental studies show that the proposed technique is simple, easy to implement, robust to noise, and outperforms the classic vector filters, as well as more recent filters.

References

1. 1)
  - 22. Jin, L., Li, D.: ‘A switching vector median filter based on the CIELAB color space for color image restoration’, Signal Process., 2007, 87, pp. 1345–1354 (doi: 10.1016/j.sigpro.2006.11.008).
2. 2)
  - 8. Ng, P.E., Ma, K.K.: ‘A switching median filter with boundary discriminative noise detection for extremely corrupted images’, IEEE Trans. Image Process., 2006, 15, pp. 1506–1516 (doi: 10.1109/TIP.2005.871129).
3. 3)
  - 23. Yuan, S.Q., Tan, Y.H.: ‘Impulse noise removal by a global-local noise detector and adaptive median filter’, Signal Process., 2006, 86, pp. 2123–2128 (doi: 10.1016/j.sigpro.2006.01.009).
4. 4)
  - 6. Allende, H., Galbiati, J.: ‘A non-parametric filter for image restoration using cluster analysis’, Pattern Recognit. Lett., 2004, 25, pp. 841–847 (doi: 10.1016/j.patrec.2004.01.009).
5. 5)
  - 4. Perona, P., Malik, J.: ‘Scale-space and edge detection using anisotropic diffusion’, IEEE Trans. Pattern Anal. Mach. Intell., 1990, 12, (7), pp. 629–639 (doi: 10.1109/34.56205).
6. 6)
  - 3. Lukac, R., Smolka, B., Martin, K., et al: ‘Vector filtering for color imaging’, IEEE Signal Process. Mag., Special Issue on Color Image Processing, 2005, 22, pp. 74–86.
7. 7)
  - 9. Jin, L., Li, D.: ‘An efficient color impulse detector and its application to color images’, IEEE Signal Process. Lett., 2007, 14, pp. 397–400 (doi: 10.1109/LSP.2006.887840).
8. 8)
  - 28. Yuksel, M.E.: ‘A hybrid neuro-fuzzy for edge preserving restoration of images corrupted by impulse noise’, IEEE Trans. Image Process., 2006, 15, pp. 928–936 (doi: 10.1109/TIP.2005.863941).
9. 9)
  - 18. Smolka, B., Lukac, R., Chydzinski, A., et al: ‘Fast adaptive similarity based impulsive noise reduction filter’, Real-Time Imaging, Special Issue on Spectral Imaging, 2003, 9, pp. 261–276 (doi: 10.1016/j.rti.2003.09.015).
10. 10)
  - 36. Aubert, G., Kornprobst, P.: ‘Mathematical problems in image processing’ (Springer, 2006).
11. 11)
  - 24. Garnett, R., Huegerich, T., Chui, C., et al: ‘A universal noise removal algorithm with an impulse detector’, IEEE Trans. Image Process., 2005, 14, pp. 1747–1754 (doi: 10.1109/TIP.2005.857261).
12. 12)
  - 14. Chan, R.H., Chung-Wa, H., Nikolova, M.: ‘Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization’, IEEE Trans. Image Process., 2005, 14, pp. 1479–1485 (doi: 10.1109/TIP.2005.852196).
13. 13)
  - 10. Lin, T.C., Yu, P.T.: ‘Partition fuzzy median filter based on fuzzy rules for image restoration’, Fuzzy Sets Syst., 2004, 147, pp. 75–97 (doi: 10.1016/S0165-0114(03)00209-4).
14. 14)
  - 32. Varghese, J.: ‘Adaptive switching rank-ordered impulse noise filters: new techniques, results, and analysis’, Int. J. Imaging Sci. Eng., 2007, 1, (2), pp. 52–59.
15. 15)
  - 15. Gallegos-Funes, F.J., Ponomaryov, V.: ‘Real-time image filtering scheme based on robust estimators in presence of impulse noise’, Real-Time Imaging, 2004, 10, pp. 69–80 (doi: 10.1016/j.rti.2004.02.002).
16. 16)
  - 7. Alajlan, N., Kamel, M., Jernigan, E.: ‘Detail preserving impulsive noise removal’, Signal Process Image Commun., 2004, 19, pp. 993–1003 (doi: 10.1016/j.image.2004.08.003).
17. 17)
  - 29. Hanji, G., Latte, M.V.: ‘Detail preserving fast median based filter’, J. Adv. Comput. Sci. Technol., 2012, 1, (4), pp. 195–206 (doi: 10.14419/jacst.v1i4.248).
18. 18)
  - 11. Schulte, S., De Witte, V., Nachtegael, M., et al: ‘Fuzzy random impulsive noise reduction method’, Fuzzy Sets Syst., 2007, 158, pp. 270–283 (doi: 10.1016/j.fss.2006.10.010).
19. 19)
  - 17. Morillas, S., Gregori, V., Peris-Fajarnés, G., et al: ‘A fast impulsive noise color image filter using fuzzy metrics’, Real-Time Imaging, 2005, 11, pp. 417–428 (doi: 10.1016/j.rti.2005.06.007).
20. 20)
  - 16. Lukac, R.: ‘Adaptive color image filtering based on center weighted vector directional filters’, Multidimens. Syst. Signal Process., 2004, 15, pp. 169–196 (doi: 10.1023/B:MULT.0000017024.66297.a0).
21. 21)
  - 38. Hassan, M., Bhagvati, C.: ‘Structural similarity measure for color images’, Int. J. Comput. Appl., 2012, 43, (14), pp. 7–12.
22. 22)
  - 21. Dong, Y., Xu, S.: ‘A new directional weighted median filter for removal of random-valued impulse noise’, IEEE Signal Process. Lett., 2007, 14, pp. 193–196 (doi: 10.1109/LSP.2006.884014).
23. 23)
  - 37. Weickert, J.: ‘Coherence-enhancing diffusion filtering’, Int. J. Comput. Vis., 1999, 31, pp. 111–127 (doi: 10.1023/A:1008009714131).
24. 24)
  - 25. Shen, Y., Barner, K.E.: ‘Fast adaptive optimization of weighted vector median filters’, IEEE Trans. Signal Process., 2006, 54, pp. 2497–2510 (doi: 10.1109/TSP.2006.874028).
25. 25)
  - 19. Morillas, S.: ‘Fuzzy metrics and peer groups for impulsive noise reduction in color images’. Proc. 14th European Signal Processing Conf. EUSIPCO2006, Florence, Italy, 2006.
26. 26)
  - 12. Lukac, R., Plataniotis, K.N., Venetsanopoulos, A.N., et al: ‘A statistically-switched adaptive vector median filter’, J. Intell. Robot. Syst., 2005, 42, pp. 361–391 (doi: 10.1007/s10846-005-1730-2).
27. 27)
  - 35. Peris-Fajarnés, G., Roig, B., Vidal, A.: ‘Rank-ordered differences statistic based switching vector filter’, LNCS, 2006, 4141, pp. 74–81.
28. 28)
  - 27. Nie, Y., Barner, K.E.: ‘The fuzzy transformation and its application in image processing’, IEEE Trans. Image Process., 2006, 15, pp. 910–927 (doi: 10.1109/TIP.2005.863111).
29. 29)
  - 31. Suganthi, A., Senthilmurugan, M.: ‘Comparative study of various impulse noise reduction techniques’, Int. J. Eng. Res. Appl., 2013, 3, (5), pp. 1302–1306.
30. 30)
  - 1. Tukey, J.W.: ‘Nonlinear (nonsuperposable) methods for smoothing data’. Proc. Congr. Rec. EASCOM, 1974, vol. 74, pp. 673–681.
31. 31)
  - 5. Plataniotis, K.N., Venetsanopoulos, A.N.: ‘Color Image processing and applications’ (Springer-Verlag, 2000).
32. 32)
  - 4. Lukac, R., Plataniotis, K.N.: ‘A taxonomy of color image filtering and enhancement solutions’, in Hawkes, P.W. (Ed.): ‘Advances in imaging and electron physics’ (Elsevier, 2006), vol. 140, pp. 187–264.
33. 33)
  - 20. Smolka, B., Chydzinski, A.: ‘Fast detection and impulsive noise removal in color images’, Real-Time Imaging, 2005, 11, pp. 389–402 (doi: 10.1016/j.rti.2005.07.003).
34. 34)
  - 33. Gonzalez, R.C., Woods, R.E.: ‘Digital image processing’ (Addison Wesley, 1992).
35. 35)
  - 26. Lukac, R., Plataniotis, K.N., Smolka, B., et al: ‘cDNA microarray image processing using fuzzy vector filtering framework’, Fuzzy Sets Syst. Special Issue on Fuzzy Sets and Systems in Bioinformatics, 2005, 152, pp. 17–35.
36. 36)
  - 13. Srinivasan, K.S., Ebenezer, D.: ‘A new fast and efficient decision-based algorithm for removal of high-density impulse noises’, IEEE Signal Process. Lett., 2007, 14, pp. 189–192 (doi: 10.1109/LSP.2006.884018).
37. 37)
  - 2. Astola, J., Haavisto, P., Neuvo, Y.: ‘Vector median filters’, Proc. IEEE., 1990, 78, pp. 678–689 (doi: 10.1109/5.54807).
38. 38)
  - 30. Ibrahim, H., Kong, N.S.P., Ng, T.F.: ‘Simple adaptive median filter for the removal of impulse noise from highly corrupted images’, IEEE Trans. Consum. Electron., 2008, 54, (4), pp. 1920–1927 (doi: 10.1109/TCE.2008.4711254).

Login

Not registered yet?

Share

Tools

Login to add to favourites

Key

Localised rank-ordered differences vector filter for suppression of high-density impulse noise in colour images

References

Related content