Noise reduction of High-Resolution SAR image over Vegetation and Urban Areas by means of Savitzky-Golay filter

Authors

  • Shyamvir Singh Sikarwar, Seema Shukla, Priya Jha

Keywords:

SAR (synthetic aperture radar), DEMs (digital elevation models) Electromagnetic (EM), Brute force thresholding, Directional smoothing, Direction dependent mask, undecimated wavelet transformation

Abstract

In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, savizat filter (which is an adaptive filter) and mean filter. Algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. The reduction of speckle is necessary for any further processing of SAR image. A new adaptive filtering algorithm is proposed to remove speckle in SAR images in this paper.

References

Jin-wei Li, Zhen-fang Li, Zheng Bao, Ying-long Hou, and Zhiyong Suo, “Noise Filtering of High-Resolution Interferograms Over Vegetation and Urban Areas With a Refined Nonlocal Filter” IEEE Geos. Remote Sensing Lett., vol. 12, no. 1, pp. 77-81, Jan. 2015.

Jiao Guo, Weitao Zhang, Yanyang Liu, Longsheng Fu, “Improving the accuracy of local frequency estimation for interferometric synthetic aperture radar interferogram noise filtering considering large co-registration errors” IET Radar Sonar Navig., vol. 8, iss. 6, pp. 676-684, 2014.

Gaohuan Lv, Junfeng Wang, and Xingzhao Liu, “Synthetic Aperture Radar Based Ground Moving Target Indicator Using Symmetrical Doppler Rate Matched Filter Pairs”, IEEE pp. 962-967, 2012.

Alper Basturk, M. Emin Yuksel, “Adaptive NEURO-FUZZY Inference System for Speckle Noise Reduction in SAR Images” IEEE 2007.

C. Moloney, G. Ramponi, “Smoothing Speckled Images Using an Adaptive Rational Operator”, IEEE Signal Processing Letters, vol. 4, no. 3, March 1997.

E. Trouvé, M. Caramma, and H. Maître, “Fringe detection in noisy complex interferograms,” Appl. Opt., vol. 35, no. 20, pp. 3799-3806, Jul. 1996.

Monti Guarnieri, A., “Using topography statistics to help phase unwrapping”, IET Radar Sonar Navig., 2003, 150, (3), pp. 144-151.

Stoica, P., Nehorai, A., “MUSIC, maximum likelihood, and Cramer-Rao bound: further results and comparisons”, IEEE Trans. Acoust. Speech Signal Process., 1990, 38, (12), pp. 2140–2150.

Li, Z.F., Bao, Z., Li, H., “Image auto-coregistration and InSAR interferogram estimation using joint subspace projection”, IEEE Trans. Geosci. Remote Sens., 2006, 44, (2), pp. 288–297.

Li, H., Li, Z.F., Liao, G.S., Bao, Z., “An estimation method for InSAR interferometric phase combined with image auto-coregistration”, Sci. China, Ser. F, 2006, 49, (3), pp. 386–396.

Liu, N., Zhang, L.R., Liu, X., “Multibaseline InSAR height estimation through joint covariance matrix fitting”, IET Radar Sonar Navig., 2009, 3, (5), pp. 474–483.

Wu, N., Feng, D.Z., Li, J.X., “A locally adaptive filter of interferometric phase images”, IEEE Geosci. Remote Sens. Lett., 2006, 3, (1), pp. 73–77.

Lee, J.S., Papathanassiou, K.P., Ainsworth, T.L., “A new technique for noise filtering of SAR interferometric phase images”, IEEE Trans. Geosci. Remote Sens., 1998, 36, (5), pp. 1456–1465.

Z. F. Li, Z. Bao, H. Li, and G. S. Liao, “Image autocoregistration and InSAR interferogram estimation using joint subspace projection,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 2, pp. 288–297, Feb. 2006.

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How to Cite

Shyamvir Singh Sikarwar, Seema Shukla, Priya Jha. (2025). Noise reduction of High-Resolution SAR image over Vegetation and Urban Areas by means of Savitzky-Golay filter . International Journal of Research & Technology, 7(2), 1–4. Retrieved from https://ijrt.org/j/article/view/95

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Section

Original Research Articles

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