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ITERATIVE TECHNIQUE OF MULTIPLICATIVE NOISE REDUCTION IN DIGITAL IMAGES

Bogdan Smolka

First published: 2016-06-28https://doi.org/10.5593/sgem2016/b21/s07.035View metrics

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Title
ITERATIVE TECHNIQUE OF MULTIPLICATIVE NOISE REDUCTION IN DIGITAL IMAGES
Authors
Bogdan Smolka
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 16th International Multidisciplinary Scientific GeoConference SGEM2016, Informatics, Geoinformatics and Remote Sensing
Publisher
Stef92 Technology
Year
2016
Pages
271-278
ISSN
1314-2704
ISBN
978-619-7105-58-2
Language
en
Publication type
Conference Paper
References30

  1. Loizou C.P., Pattichis C.S., Despeckle filtering algorithms and software for ultrasound imaging, Synthesis Lectures on Algorithms and Software in Engineering, Morgan & Claypool, 2008.

  2. Lee J., Speckle analysis and smoothing of synthetic aperture radar images, Computer Graphics and Image Processing, vol. 17, pp 24-32, 1981.

  3. Kuan D., Sawchuk A., Strand T., Chavel P., Adaptive restoration of images with speckle, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, pp 373-383 , 1987.

  4. Frost V. S., Stiles J. A., Shanmugan K. S., and 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, pp 157-166, 1982.

  5. Lopes A., Nezry E., Touzi R., Laur, H., Structure detection and statistical adaptive speckle filtering in SAR images, International Journal of Remote Sensing, vol. 14, pp 1735-1758, 1993.

  6. Perona P., Malik J., Scale-space and edge detection using anisotropic di ffusion, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 12, pp 629-639, 1990.

  7. Yu Y. and Acton S.T., Speckle reducing anisotropic diffusion, IEEE Transactions on Image Processing, vol. 11/issue 11, pp 1260-1270, 2002.

  8. Gupta S., Chauhan R.C., Sexana S.C., Wavelet-based statistical approach for speckle reduction in medical ultrasound images, Medical and Biological Engineering and Computing, vol. 42/issue 2, pp 189 -192, 2004.

  9. Tomasi, C., Manduchi, R., Bilateral filtering for gray and color images, Proceedings of the Sixth International Conference on Computer Vision, pp 839-846, 1998.

  10. Donoho D. L., Johnstone I. M., Ideal spatial adaptation by wavelet shrinkage , Biometrika, vol. 81, pp 425-455, 1994.

  11. Donoho D. L. , Johnstone I. M., Adapting to unknown smoothness via wavelet shrinkage, Journal of the American Statistical Association, pp 1200-1224, 1995.

  12. Chang S.G., Yu B., Vetterli M., Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. on Image Processing, vol. 9/issue 9, pp 1532-1546, 2000.

  13. Prakash K. B., Babu R.V., Gopal B.V., Image independent filter for removal of speckle noise, Int. Journal of Computer Science Issues, vol. 8/issue 5, 196-201, 2011.

  14. Eskicioglu A.M., Fisher P.S., Image quality measures and their performance , IEEE Transactions on Communications, vol. 43/issue 12, pp 2959-2965, 1995.

  15. Avcibas I., Sankur B., Sayood K., Statistical evaluation of image quality measures, Journal of Electronic Imaging, vol. 11/issue 2, pp 206-223, 2002. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

  16. Loizou C.P., Pattichis C.S., Despeckle filtering algorithms and software for ultrasound imaging, Synthesis Lectures on Algorithms and Software in Engineering, Morgan & Claypool, 2008.

  17. Lee J., Speckle analysis and smoothing of synthetic aperture radar images, Computer Graphics and Image Processing, vol. 17, pp 24-32, 1981.

  18. Kuan D., Sawchuk A., Strand T., Chavel P., Adaptive restoration of images with speckle, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, pp 373-383 , 1987.

  19. Frost V. S., Stiles J. A., Shanmugan K. S., and 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, pp 157-166, 1982.

  20. Lopes A., Nezry E., Touzi R., Laur, H., Structure detection and statistical adaptive speckle filtering in SAR images, International Journal of Remote Sensing, vol. 14, pp 1735-1758, 1993.

  21. Perona P., Malik J., Scale-space and edge detection using anisotropic di ffusion, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 12, pp 629-639, 1990.

  22. Yu Y. and Acton S.T., Speckle reducing anisotropic diffusion, IEEE Transactions on Image Processing, vol. 11/issue 11, pp 1260-1270, 2002.

  23. Gupta S., Chauhan R.C., Sexana S.C., Wavelet-based statistical approach for speckle reduction in medical ultrasound images, Medical and Biological Engineering and Computing, vol. 42/issue 2, pp 189 -192, 2004.

  24. Tomasi, C., Manduchi, R., Bilateral filtering for gray and color images, Proceedings of the Sixth International Conference on Computer Vision, pp 839-846, 1998.

  25. Donoho D. L., Johnstone I. M., Ideal spatial adaptation by wavelet shrinkage , Biometrika, vol. 81, pp 425-455, 1994.

  26. Donoho D. L. , Johnstone I. M., Adapting to unknown smoothness via wavelet shrinkage, Journal of the American Statistical Association, pp 1200-1224, 1995.

  27. Chang S.G., Yu B., Vetterli M., Adaptive wavelet thresholding for image denoising and compression. IEEE Trans. on Image Processing, vol. 9/issue 9, pp 1532-1546, 2000.

  28. Prakash K. B., Babu R.V., Gopal B.V., Image independent filter for removal of speckle noise, Int. Journal of Computer Science Issues, vol. 8/issue 5, 196-201, 2011.

  29. Eskicioglu A.M., Fisher P.S., Image quality measures and their performance , IEEE Transactions on Communications, vol. 43/issue 12, pp 2959-2965, 1995.

  30. Avcibas I., Sankur B., Sayood K., Statistical evaluation of image quality measures, Journal of Electronic Imaging, vol. 11/issue 2, pp 206-223, 2002. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

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