Skip to main content

An Analog–Digital Hardware for L-Estimate Space-Varying Image Filtering

Circuits, Systems, and Signal Processing volume 35, pages 409–420 (2016)Cite this article

Abstract

An analog–digital hardware solution for implementation of the L-estimate space-varying filtering has been proposed. The considered filter form is based on the robust space/spatial-frequency representation and provides efficient denoising of two-dimensional signals/images corrupted by heavy-tailed noise. Moreover, for images with fast-varying details and textures, the L-estimate filtering outperforms the commonly used filters. However, it requires significant processing time, since the space/spatial-frequency representation is calculated for each pixel, on a window by window basis. Therefore, in order to make it feasible for practical applications, a fast implementation of L-estimate space-varying filtering is proposed using a combined analog–digital approach. It provides efficient real-time processing of images corrupted by strong mixed Gaussian and impulse noise.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price includes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. N. Alajlan, M. Kamel, E. Jermigam, Detail preserving impulsive noise removal. Signal Process. Image Commun. 19(10), 993–1003 (2004)

    Article  Google Scholar 

  2. N.A. Anderson, Instrumentation for Process Management and Control, 3rd edn. (CRC Press, Boca Raton, 1997)

    Google Scholar 

  3. X. Chen, Z. Li, A low-power CMOS analog multiplier. IEEE Trans. Circuits Syst. II Express Briefs 53(2), 100–104 (2006)

    Article  Google Scholar 

  4. M. Cherniakov, An Introduction to Parametric Digital Filters and Oscillators (Wiley, New York, 2007)

    Google Scholar 

  5. I. Djurović, L. Stanković, J.F. Böhme, Robust L-estimation based forms of signal transforms and time-frequency representations. IEEE Trans. Signal Process. 51(7), 1753–1761 (2003)

    MathSciNet  Article  Google Scholar 

  6. P. Getreuer, Rudin–Osher–Fatemi total variation denoising using split Bregman. Image Process. 2, 74–95 (2012)

    Article  Google Scholar 

  7. A.B. Hamza, H. Krim, Image denoising: a nonlinear robust statistical approach. IEEE Trans. Signal Process. 49(12), 3045–3054 (2001)

    Article  Google Scholar 

  8. http://www.utdallas.edu/~kamran/AD633.pdf

  9. http://datasheetcatalog.com/datasheets_pdf/M/P/Y/5/MPY534.shtml

  10. X. Jiang, Iterative truncated arithmetic mean filter and its properties. IEEE Trans. Image Process. 21(4), 1537–1547 (2012)

    MathSciNet  Article  Google Scholar 

  11. M. Juneja, R. Mohana, An improved adaptive median filtering method for impulse noise detection. Int. J. Recent Trends Eng. 1(1), 274–278 (2009)

    Google Scholar 

  12. Z. Miao, X. Jiang, Further properties and a fast realization of the iterative truncated arithmetic mean filter. IEEE Trans. Circuits Syst. II 59(11), 810–814 (2012)

    Article  Google Scholar 

  13. Z. Miao, X. Jiang, Weighted iterative truncated mean filter. IEEE Trans. Signal Process. 61(16), 4149–4160 (2013)

    MathSciNet  Article  Google Scholar 

  14. Z. Miao, X. Jiang, Additive and exclusive noise suppression by iterative trimmed and truncated mean algorithm. Signal Process. 99, 147–158 (2014)

    Article  Google Scholar 

  15. A. Naderi, A. Khoei, K. Hadidi, H. Ghasemzadeh, A new high speed and low power four-quadrant CMOS analog multiplier in current mode. Int. J. AEU Electron. Commun. 63, 769–775 (2009)

    Article  Google Scholar 

  16. I. Orović, N. Žarić, S. Stanković, Robust space/spatial-frequency based filtering of images in the presence of heavy tailed noise. 20th International Conference on Computer Graphics and Vision, (2010), pp. 116–119

  17. E. Otez, R.J.P. Figueiredo, Adaptive alpha-trimmed mean filters under deviations from assumed noise model. IEEE Trans. Image Process. 13(5), 627–639 (2004)

    Article  Google Scholar 

  18. I. Pitas, A.N. Venetsanopoulos, Nonlinear Digital Filters: Principles and Applications (Kluwer, Norwell, 1990)

    MATH  Book  Google Scholar 

  19. L.I. Rudin, S. Osher, E. Fatemi, Nonlinear total variation based noise removal algorithms. Phys. D 60, 259–268 (1992)

    MATH  MathSciNet  Article  Google Scholar 

  20. L. Stanković, S. Stanković, I. Djurović, Space/spatial-frequency analysis based filtering. IEEE Trans. Signal Process. 48(8), 2343–2352 (2000)

    MATH  MathSciNet  Article  Google Scholar 

  21. G. Wang, D. Li, W. Pan, Z. Zang, Modified switching median filter for impulse noise removal. Signal Process. 90(12), 3213–3218 (2010)

    MATH  Article  Google Scholar 

  22. P.S. Windyga, Fast impulsive noise removal. IEEE Trans. Image Process. 10, 173–179 (2001)

    Article  Google Scholar 

  23. N. Zarić, N. Lekić, S. Stanković, An implementation of the L-estimate distributions for analysis of signals in heavy-tailed noise. IEEE Trans. Circuits Syst. II 58(7), 427–431 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Montenegro, 81000, Podgorica, Montenegro

    Irena Orović, Nedjeljko Lekić & Srdjan Stanković

Authors
  1. Irena Orović
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nedjeljko Lekić
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Srdjan Stanković
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Irena Orović.

Additional information

This work is supported by the Montenegrin Ministry of Science, Project Grant: CS-ICT “New ICT Compressive sensing based trends applied to: multimedia, biomedicine and communications”.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Orović, I., Lekić, N. & Stanković, S. An Analog–Digital Hardware for L-Estimate Space-Varying Image Filtering. Circuits Syst Signal Process 35, 409–420 (2016). https://doi.org/10.1007/s00034-015-0083-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-015-0083-8

Keywords

  • Analog–digital hardware
  • Robust space/spatial-frequency distributions
  • L-estimate forms
  • Robust space-varying filtering