Enhancing Biomedical Images Using the UFIR Filters with Recursive Responses

  • Luis J. Morales-Mendoza
  • Rene F. Vázquez-Bautista
  • Mario González-Lee
  • M. Ibarra-Manzano
  • Y. Shmaliy
  • J. Martínez-Castillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)

Abstract

In this paper we present a novel computational scheme to determine the impulse response of the UFIR filters. A recursive form of impulse response is developed using the theory of the discrete orthogonal polynomials. An example of an enhanced of medical image is considered to compare its performance versus the matrix formulation of the impulse response UFIR filters. Finally, some quantitative and qualitative evaluations are carried out to verify its efficiency based on RMSE analysis.

Keywords

UFIR filters biomedical images discrete orthogonal polynomials recurrent relation 

References

  1. 1.
    Najarian, K., Splinter, R.: Biomedical Signal and Image Processing. CRC Taylor & Francis Group, New York (2006)Google Scholar
  2. 2.
    Jan, H.: Medical Image Processing, Reconstruction and Restoration – Concepts and Methods. CRC Taylor & Francis Group, New York (2006)Google Scholar
  3. 3.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, New Jersey (2002)Google Scholar
  4. 4.
    Jähne, B.: Digital Image Processing. Springer, Berlin (2002)MATHCrossRefGoogle Scholar
  5. 5.
    Pitas, I., Venetsanopoulos, A.: Nonlinear Digital Filters – Principles and Applications. Kluwer Academic Publishers (1990)Google Scholar
  6. 6.
    Kalouptsidis, N., Theodoridis, S.: Adaptive System Identification and Signal Processing Algorithms. Prentice Hall (1993)Google Scholar
  7. 7.
    Astola, J., Kuosmanen, P.: Fundamentals of Nonlinear Digital Filters. CRC Press (1997)Google Scholar
  8. 8.
    Shmaliy, Y.: An unbiased FIR filter for TIE model of a local clock in applications to GPS-based timekeeping. IEEE Trans. on Ultrasonic, Ferroelectrics and Frequency Control 53(5), 862–870 (2006)CrossRefGoogle Scholar
  9. 9.
    Shmaliy, Y.: An unbiased p-step predictive FIR filter for a class of noise-free discrete time models with independently observed states. Signal, Image & Video Processing 3(2), 127–135 (2009)CrossRefGoogle Scholar
  10. 10.
    Shmaliy, Y.: GPS-based Optimal FIR Filtering of Clock Models. NOVA Science Publishers, New York (2009)Google Scholar
  11. 11.
    Shmaliy, Y., Morales-Mendoza, L.J.: FIR smoothing of discrete-time polynomial signals in state space. IEEE Trans. on Signal Processing 58(5), 2544–2555 (2010)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Morales-Mendoza, L.J., Shmaliy, Y., Ibarra-Manzano, O.G., Arceo-Miquel, L.J., Montiel-Rodriguez, M.: Moving Average Hybrid FIR Filter in Ultrasound Image Processing. In: IEEE Proceeding of 18th CONIELECOMP, Puebla, México, pp. 160–164 (2008)Google Scholar
  13. 13.
    Morales-Mendoza, L.J., Shmaliy, Y.: Moving Average Hybrid Filter to the EnhancingUltrasound Image Processing. IEEE Trans. on America Latina 8(1), 9–16 (2010)CrossRefGoogle Scholar
  14. 14.
    Morales-Mendoza, L.J., Shmaliy, Y., Ibarra-Manzano, O.G.: Enhancing Ultrasound Images using Hybrid FIR Structures. In: Image Process, ch. 16, pp. 287–310. In Tech, Vienna (2009)Google Scholar
  15. 15.
    Morales-Mendoza, L.J., Shmaliy, Y., Vázquez-Bautista, R.F., Ibarra-Manzano, O.G.: Smoothing of ultrasound images with the p-lag FIR structures. In: WSEAS Proceeding of 10th SIP, Canary Islands, Spain, pp. 47–52 (2011)Google Scholar
  16. 16.
    Morales-Mendoza, L.J., Vázquez-Bautista, R.F., Morales-Mendoza, E., Shmaliy, Y.: Speckle noise reduction in ultrasound imaging using the key points in low degree unbiased FIR filters. Computación y Sistemas IPN 16(3), 287–295 (2012)Google Scholar
  17. 17.
    Morales-Mendoza, L.J., Vázquez-Bautista, R.F., Morales-Mendoza, E., Shmaliy, Y., Gamboa-Rosales, H.: A new recursive scheme of the unbiased FIR filter to image processing. Procedia Engineering 35, 202–209 (2012)CrossRefGoogle Scholar
  18. 18.
    Morales-Mendoza, L.J., Shmaliy, Y., Vázquez-Bautista, R.F., Ibarra-Manzano, O.G., Morales-Mendoza, E.: Ultrasound images processing using the recursive p-step unbiased FIR filter. In: WSEAS Proceeding of 12th ISCGAV, Istanbul, Turkey, pp. 100–106 (2012)Google Scholar
  19. 19.
    Morales-Mendoza, L.J., Shmaliy, Y., González-Lee, M., Morales-Mendoza, E., Varguez-Fernández, R.: Toward to recurrent form of the impulse response of UFIR filters. Procedia Technology (in press, 2013)Google Scholar
  20. 20.
    Gamboa-Rosales, H., Morales-Mendoza, L.J., Shmaliy, Y.: Unbiased impulse responses – a class of discrete orthogonal polynomials. ICIC Express Letters 7(7), 2005–2010 (2013)Google Scholar
  21. 21.
    Morales-Mendoza, L.J., Gamboa-Rosales, H., Shmaliy, Y.: A new class of discrete orthogonal polynomials for blind fitting of finite data. Signal Processing 93(7), 1785–1793 (2013)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Luis J. Morales-Mendoza
    • 1
  • Rene F. Vázquez-Bautista
    • 1
  • Mario González-Lee
    • 1
  • M. Ibarra-Manzano
    • 2
  • Y. Shmaliy
    • 2
  • J. Martínez-Castillo
    • 1
  1. 1.FIECUniversidad VeracruzanaPoza RicaMexico
  2. 2.DICISUniversidad de GuanajuatoSalamanca Gto.Mexico

Personalised recommendations