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Adaptive progressive filter to remove impulse noise in highly corrupted color images

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Abstract

In this paper, an adaptive progressive filtering (APF) technique with low computational complexity is proposed for removing impulse noise in highly corrupted color images. Color images that are corrupted with impulse noise are generally filtered by applying a vector-based approach. Vector-based methods tend to cluster the noise and receive a lower noise reduction performance when the noise ratio is high. To improve the performance, in the proposed technique, a new reliable estimation of impulse noise intensity and noise type is made initially, and then a progressive restoration mechanism is devised, using multi-pass non-linear operations with selected processing windows adapted to the estimation. The effect of impulse detection based on geometric characteristics and features of the corrupt pixel/pixel regions and the exact estimation of impulse noise intensity and type are used in the APF to efficiently support the progressive filtering mechanism. Through experiments conducted using a range of color images, the proposed filtering technique has demonstrated superior performance to that of well-known benchmark techniques, in terms of standard objective measurements, visual image quality, and the computational complexity.

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References

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

    Article  Google Scholar 

  2. Trahania P.E., Venetsanopoulos A.N.: Vector direction filter: a new class of multichannel image processing filter. IEEE trans. Image Process. 2(4), 528–534 (1993)

    Article  Google Scholar 

  3. Karakos, D.G., Trahania, P.E.: Combining vector median and vector direction filters: the directional-distance filter. In: Proceedings of the IEEE International Conference on Image Processing (ICIP’95), vol. 1, pp. 171–174. Washington, DC (1995)

  4. Chen T., Wu H.: Adaptive impulse detection using center-weighted median filter. Signal Process. Lett. 8(1), 1–3 (2001)

    Article  Google Scholar 

  5. Eng H.-L., Ma K.-K.: Noise adaptive soft-switching median filter. IEEE Trans. Image Process. 10, 242–251 (2001)

    Article  MATH  Google Scholar 

  6. Wang Z., Zhang D.: Progressive switching median filter for removal of impulsive noise from high corrupted images. IEEE Trans. Circuits Syst. II. 46, 78–80 (1999)

    Article  Google Scholar 

  7. Hore E.S., Qiu B., Wu H.R.: Prediction based image restoration using a multiple window configuration. Opt. Eng. 41(8), 1855–1865 (2002)

    Article  Google Scholar 

  8. Kenney C., Deng Y., Manjunath B.S., Hewer G.: Peer group image enhancement. IEEE Trans. Image Process. 10(2), 326–334 (2001)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  Google Scholar 

  10. Chen, S., Yang, X.: A Variational Method with a Noise Detector for Impulse Noise Removal. Scale Space and Variational Methods in Computer Vision Lecture Notes in Computer Science, vol. 4485/2007, pp. 442–450. (2007)

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

    Article  Google Scholar 

  12. Lukac R., Smolka B., Plataniotis K.N., Venetsanopoulos A.N.: Selection weighted vector directional filter. Comput. Vis. Image Underst. 94(1–3), 140–167 (2004)

    Article  Google Scholar 

  13. Lukac R.: Adaptive color image filtering based on center weighted vector direction filters. Multidiment. Syst. Signal Process. 15(2), 169–196 (2004)

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  15. Hu, C., Lui, S.H.: Variational approach for restoring random-valued impulse noise. Numerical Analysis and Its Applications Lecture Notes in Computer Science, vol. 3401/2005, pp. 312–319. (2005)

  16. Cai J.-F., Chan R.H., Nikolova M.: Fast two-phase image deblurring under impulse noise. J. Math. Imaging Vis. 36, 46–53 (2010)

    Article  MathSciNet  Google Scholar 

  17. Liu J., Huang H., Huan Z., Zhang H.: Adaptive variational method for restoring color images with high density impulse noise. Int. J. Comput. Vis. 90, 131–149 (2010)

    Article  Google Scholar 

  18. Celebi M.E., Kingravi H.A., Aslandogan Y.A.: Nonlinear vector filtering for impulsive noise removal from color images. J. Electron. Imaging. 16(3), 033008:1–033008:21 (2007)

    Google Scholar 

  19. Camacho J., Morillas S., Latorre P.: Efficient impulsive noise suppression based on statistical confidence limits. J. Imaging Sci. Technol. 50(5), 427–436 (2006)

    Article  Google Scholar 

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

    Article  Google Scholar 

  21. Ma Z., Wu H.R., Qiu B.: An structure adaptive hybrid vector filter for the restoration of digital color images. IEEE Trans. Image Process. 14(12), 1990–2001 (2005)

    Article  Google Scholar 

  22. Hore, E.S., Qiu B., Wu H.R.: Improved color image vector filtering using fuzzy noise detection. Opt. Eng. 42(6), 1656–1664 (2003)

    Article  Google Scholar 

  23. Ponomaryov V.I., Gallegos-funes F.J., Rosales-Silva A.: Realtime color imaging based on RM-filters for impulsive noise reduction. J. Imaging Sci. Technol. 49(3), 205–219 (2005)

    MathSciNet  Google Scholar 

  24. Vardavoulia M.I., Andreadis I., Tsalides P.: A new vector median filter for color image processing. Pattern Recognit. Lett. 22(6–7), 675–689 (2001)

    Article  MATH  Google Scholar 

  25. Chatzis V., Pitas I.: Fuzzy scalar and vector median filters based on fuzzy distances. IEEE Trans. Image Process. 8(5), 731–734 (1999)

    Article  Google Scholar 

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

    Article  Google Scholar 

  27. Smolka B., Lukac R., Chydzinski A., Plataniotis K.N., Wojciechowski W.: Fast adaptive similarity based impulsive noise reduction filter. Real-Time Imaging. 9(4), 261–276 (2003)

    Article  Google Scholar 

  28. Schulte S., Morillas S., Gregori V., Kerre E.E.: A new fuzzy color correlated impulsive noise reduction method. IEEE Trans. Image Process. 16(10), 2565–2575 (2007)

    Article  MathSciNet  Google Scholar 

  29. Xu Z., Wu H.R., Qiu B., Yu X.: Geometric features based filtering for suppression of impulse noise in color images. IEEE Trans. Image Process. 18(8), 1742–1759 (2009)

    Article  MathSciNet  Google Scholar 

  30. Plataniotis, K.N., Venetsanopoulos, A.N. (eds.): Color image processing and applications. Springer, Berlin (2000)

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  33. Ma Z., Wu H.R., Feng D.: Partition based vector filtering technique for suppression of noise in digital color images. IEEE Trans. on Image Processing 15(8), 2324–2342 (2006)

    Article  Google Scholar 

  34. Image Database: http://r0k.us/graphics/kodak and http://www.hlevkin.com

  35. Pitas I., Venetsanopoulos A.N.: Nonlinear Digital Filter: Principles and Applications. Kluwer, Norwell, MA (1990)

    MATH  Google Scholar 

  36. Bronshtein I.N., Semendyayev K.A., Musiol G., Muehing H.: Handbook of Mathematics, Fifth Edition. Springer, New York (2007)

    Google Scholar 

  37. Plataniotis K.N., Sri V., Androutsos D., Venetsanopoulos A.N.: An adaptive nearest neighbor multichannel filter. IEEE Tans. Circuits Syst Video Technol. 6(6), 699–703 (1996)

    Article  Google Scholar 

  38. Ma, Z., Wu, H.R.: A histogram based adaptive vector filter for color image restoration. In: Proceedings of the IEEE ICICS-PCM’03, pp. 1A3.4.1–5. Singapore, 15–18 Dec 2003

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, RMIT University, Melbourne, VIC, Australia

    Zhengya Xu, Hong Ren Wu & Xinghuo Yu

  2. Faculty of Information Technology, Monash University, Clayton, VIC, Australia

    Bin Qiu

Authors
  1. Zhengya Xu
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  2. Hong Ren Wu
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  3. Xinghuo Yu
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  4. Bin Qiu
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Correspondence to Zhengya Xu.

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Xu, Z., Wu, H.R., Yu, X. et al. Adaptive progressive filter to remove impulse noise in highly corrupted color images. SIViP 7, 817–831 (2013). https://doi.org/10.1007/s11760-011-0271-3

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  • DOI: https://doi.org/10.1007/s11760-011-0271-3

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