Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Despeckling of Synthetic Aperture Radar Images Using Inner Product Spaces in Undecimated Wavelet Domain
Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak, Athar Mohsin, UmarFarooq
Abstract:
This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely directional smoothing filter which is an additional step. Proposed method does not need any noise estimation and thresholding technique. More over proposed method gives good results on both single polarimetric and fully polarimetric SAR images.Keywords: Directional Smoothing, Inner product, Length ofvector, Undecimated wavelet transformation.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1082913
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614References:
[1] Mario Mastriani, "New Wavelet-Based Super resolution Algorithm for Speckle Reduction in SAR Images". International journal of computer science (IJCS), Vol 1, ISSN 1306-4428-2006, pp.291-298, 2006.
[2] Saevarsson, B.B, Sveinsson, J.R, Benediktsson J.A, "Combined Wavelet and Curvelet Denoising of SAR Images", IEEE Transactions on Geosciences and Remote Sensing, Vol 6, pp. 4235-4238, Sept 2004.
[3] Guozhong Chen, Xingzhao Liu "Wavelet-Based Despeckling SAR Images Using Neighbouring Wavelet Coefficients" IEEE conference on RADAR, Vol 3,pp.212-216,2005.
[4] Guozhong Chen, Xingzhao Liu, "An Improved Wavelet -Based Method for SAR image Denoising Using Data Fusion" IEEE conference on RADAR, Vol. 6, pp. 818-822, April 2006.
[5] D. Lee Fugal , "Conceptual Wavelets in Digital Signal Processing", 2007.
[6] M. I. H. Bhuiyan, M. Omair Ahmed M. N. S. Swamy, "Wavelet-based Spatially Adaptive Method for Despeckling SAR Images", IEEE International Symposium on Circuits and Systems, ISCAS, Vol. 10, pp.1109-1112, May 2006.
[7] Sheng Guofang ,Hu Xin , Jiao Licheng, "SAR Image Denoising based on Data Fusion", Proceedings of the fifth computational intelligence and multimedia applications ICCIMA, Vol 10, pp.143-148,Sept 2003.
[8] Aglika Gyaourova "Undecimated Wavelet Transforms for Image Denoising" center for applied scientific computing, Lawrence Livermore nation laboratory, November 19, 2002.
[9] D.L .Donoho, "Denoising by soft Thresholding," IEEE Trans. on Inform Theory, vol. 41, pp. 613-627, May 1995.
[10] H.S. Tan, "Denoising of Noise Speckle in Radar Image", Oct 2001.
[11] H. Guo, J.E. Odegard, M. Lang, R.A. Gopinath, I. Selesnick, and C.S.Burrus, "Speckle reduction via wavelet shrinkage with application to SAR based ATD/R," Technical Report CML TR94-02, CML, Rice University, Houston, 1994.
[12] D.L. Donoho and I.M. Johnstone, "Adapting to unknown smoothness via wavelet shrinkage," Journal of the American Statistical Association, vol. 90, no. 432, pp. 1200-1224, 1995.
[13] S.G. Chang, B. Yu, and M. Vetterli, "Adaptive wavelet thresholding for image denoising and compression," IEEE Transactions on Images Processing, vol 9, no. 9, pp.1532-1546, September 2000.
[14] X. P. Zhang, "Thresholding Neural Network for Adaptive Noise reduction," IEEE Transactions on Neural Networks, vol.12, no.3, pp567-584.May 2001.
[15] S. M. Yusuf, Abdul Majeed, Muhammad Amin "Mathematical Methods" 2000.
[16] Anil K. Jain "Fundamentals of Digital Image Processing.2004.