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Quasi-Gaussian DCT Filter for Speckle Reduction of Ultrasound Images

  • Slamet Riyadi
  • Mohd. Marzuki Mustafa
  • Aini Hussain
  • Oteh Maskon
  • Ika Faizura Mohd. Noh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5857)

Abstract

In recent time, ultrasound imaging is a popular modality for various medical applications. The presence of speckle noise affects difficulties on features extraction and quantitative measurement of ultrasound images. This paper proposes a new method to suppress the speckle noise while attempting to preserve the image content using combination of Gaussian filter and discrete cosine transform (DCT) approach. The proposed method, called quasi-Gaussian DCT (QGDCT) filter, is a quasi Gaussian filter in which its coefficients are derived from a selected 2-dimensional cosine basis function. The Gaussian approach is used to suppress speckle noise whereas the selected DCT approach is intended to preserve the image content. The filter will be implemented on the synthetic speckle images and the clinical echocardiograph ultrasound images. To evaluate the effectiveness of the filter, several quantitative measurements such as mean square error, peak signal to noise ration, speckle suppression index and speckle statistical analysis, are computed and analyzed. In comparison with established filters, results obtained confirmed the effectiveness of QGDCT filter in suppressing speckle noise and preserving the image content.

Keywords

Gaussian DCT speckle ultrasound image echocardiography 

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References

  1. 1.
    Lee, J.-S.: Speckle Suppression and Analysis for Synthetic Aperture Radar Images. Optical Engineering 25(5), 636–643 (1986)Google Scholar
  2. 2.
    Frost, V.S., Stiles, J.A., Shanmugan, K.S., Holtzman, J.C.: A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise. IEEE Transactions on Pattern Analysis and Machine Intelligence 4(2), 157–166 (1982)CrossRefGoogle Scholar
  3. 3.
    Grimmins, T.R.: Geometric Filter for Reducing Speckle. Opt. Eng. 25(4), 652–654 (1986)Google Scholar
  4. 4.
    Donoho, D.L.: De-noising by Soft-thresholding. IEEE Trans. Inform Theory 41, 613–627 (1995)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Dutt, V., Greenleaf, J.: Adaptive Speckle Reduction Filter for Log Compressed B-scan Images. IEEE Trans. Med. Imaging 15(6), 802–813 (1996)CrossRefGoogle Scholar
  6. 6.
    Krissian, K., Vosburgh, K., Kikinis, R., Westin, C.F.: Anisotropic Diffusion of Ultrasound Constrained by Speckle Noise Model. Tech. report. Harvard Med. School (2004)Google Scholar
  7. 7.
    Raouf, A., Lichtenegger, J.: Integrated Use of SAR and Optical Data for Coastal Zone Management. In: ERS Satellite Radar Imagery: Proceedings of the Third ERS Symposium, ESA SP-1204 (1997)Google Scholar
  8. 8.
    Petland, A., Horowitz, B.: Recovery of Non-rigid Motion and Structure. IEEE Transaction on Pattern Analysis and Machine Intelligent 13, 730–742 (1991)CrossRefGoogle Scholar
  9. 9.
    Khayam, S.A.: The Discrete Cosine Transform: A Theory and Application.Tutorial of the Dept. of Electric & Computer Engineering, Michigan State University (2003)Google Scholar
  10. 10.
    Richardson, I.E.G.: H.264 and MPEG-4 Video Compression: Video Coding for Next-generation Multimedia. John Willey & Sons, West Sussex (2003)CrossRefGoogle Scholar
  11. 11.
    Lee, J.S., Jurkevich, I., Dewaele, P., Wambacq, P., Oosterlinck, A.: Speckle Filtering of Synthetic Aperture Radar Images: A Review. RemoteSensing Review 8, 313–340 (1994)Google Scholar
  12. 12.
    Qiu, F., Berglund, J., Jensen, J.R., Thakkar, P., Ren, D.: Speckle noise reduction in SAR imagery using a local adaptive median filter. GIScience and Remote Sensing 41(3), 244–266 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Slamet Riyadi
    • 1
  • Mohd. Marzuki Mustafa
    • 1
  • Aini Hussain
    • 1
  • Oteh Maskon
    • 2
  • Ika Faizura Mohd. Noh
    • 2
  1. 1.Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBangi
  2. 2.Universiti Kebangsaan Malaysia Medical CenterKuala LumpurMalaysia

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