Speckle suppression of radar images using normalized convolution

Journal of Computer Science

Volumn 6, Issue 10, 2010, Pages 1154-1158

  Helmy, A K ^a   El Taweel, G S ^b  

^a NATIONAL AUTHORITY FOR REMOTE SENSING AND SPACE SCIENCES   (Egypt)

^b Old Campus   (Egypt)

Author keywords

Normalized convolution; SAR image; Speckle reduction

Indexed keywords

EID: 78049525040     PISSN: 15493636     EISSN: None     Source Type: Journal    
DOI: 10.3844/jcssp.2010.1154.1158     Document Type: Article

References (18)

1. Achim, A., A. Bezerianos and P. Tsakalides, 2001. Novel Bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Trans. Med. Image, 20: 772-783, http://portal.acm.org/citation.cfm?id=1279009.127 9195.
2. Aglika, G., 2002. Undecimated wavelet transforms for image denoising. University of Nevada. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.1435&rep=rep1&type=pdf.
3. Arsenault, H.H. and G. April, 2000. Properties of speckle integrated with a finite aperture and logarithmically transformed. J. Opt. Soc. Am., 66: 1160-1163. http://portal.acm.org/citation.cfm?id=1057851.1057888.
4. Donoho, D.L., 1995. Denoising by soft-thresholding. IEEE Trans. Inform. Theory, 41: 613-627. DOI: 10.1109/18.119733.
5. Fisher, R., S. Perkins, A. Walker and E. Wolfart, 2001. Median filter. INF Press. http://homepages.inf.ed.ac.uk/rbf/HIPR2/median.htm.
6. Gagnon, L. and A. Jouan, 1997. Speckle Filtering of SAR images-a comparative study between complex wavelet based and standard filters. SPIE Proc., 3169: 80-91. DOI: 10.1.1.54.3239.
7. Goodman, J.W., 1996. Some fundamental properties of speckle. J. Opt. Soc. Am., 66: 1145-1150. http://portal.acm.org/citation.cfm?id=1780209.
8. Guo, H., J.E. Odegard, M. Lang, R.A. Gopinath and I.W. Selesnick, 1994. Wavelet based speckle reduction with application to SAR based ATD/R. Proc. Int. Conf. Image Process., 1: 75-79.
9. Haralick, R.M. and L. Watson, 1981. A facet model for image data. Comput. Graph. Image Proc., 15: 113-129. DOI: 10.1109/34.19033.
10. Knutsson, H. and C.F. Westin, 1993. Normalized and differential convolution. Proceeding of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (CVPR'93), IEEE Press, New York, USA., pp: 515-523.
11. Kuan, D.T., A.A. Sawchuk, T.C. Strand and P. Chavel, 1987. Adaptive restoration of images with speckle. IEEE Trans. ASSP, 35: 373-383.
12. Lee, J.S., 1981. Speckle analysis and smoothing of synthetic aperture radar images. Comput. Graph. Image Process., 17: 24-32. DOI: 10.1016/S0146-664X(81)80005-6.
13. Mark, A.S., 1995. Noise reduction in syntactic aperture radar imagery using a morphology-based nonlinear filter. Proceeding of the Digital Image Computing: Techniques and Applications, Conference of Australian Pattern Recognition Society, (APRS'95), IEEE Press, Brisbane, pp: 661-666.
14. Melnik, V.R., V. Lukin, K. Egiazarian and J. Astola, 2000. A method of speckle removal in one-look SAR images based on lee filtering and wavelet denoising. Proceeding of the IEEE Nordic Signal Processing Symposium, (NORSIG'00), Kolmarden, Sweden, pp: 1-4.
15. Nason, G.P. and B.W. Silverman, 1995. The Stationary Wavelet Transform and Some Statistical Application. In: Wavelets and Statistics, Antoniadis, A. and G. Oppenhim (Eds.), Springer-Verlag, New York, pp: 281-299.
16. Russ, J.C., 2002. The Image Processing Handbook. 4th Edn., CRC Press, New York, ISBN: 13: 978-0849311420, pp: 732.
17. Tuan, Q.P., L.J. Van Vliet and K. Schutte, 2010. Robust fusion of irregularly sampled data using adaptive normalized convolution. EURASIP J. Applied Sig. Proc., 2006: 236-236.
18. Young, R.A., 2001. The Gaussian derivative model for spatial vision: I. Retinal mechanisms. Spat. Vis., 14: 273-293.