Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters
In this paper we introduced new wavelet based 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. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
[1] Birgir Bjorn Saevarsson,Johannes R.Sveinsson and Jon Atli
Benediktsson "Combined Wavelet and Curvelet Denoising of SAR
Images" Proceedings of IEEE 2004.
[2] Guozhong Chen,Xingzhao Liu "Wavelet-Based Despeckling SAR
Images Using Neighbouring Wavelet Cofficients." Proceedings of IEEE
2005.
[3] Guozhong Chen,Xingzhao Liu "An Improved Wavelet-based Method
for SAR Images Denoising Using Data Fusion Technique". Proceedings
of IEEE 2006.
[4] Mario Mastriani "New Wavelet-based Superresolution Algorithm for
Speckle Reduction in SAR Images" IJCS volume 1 number 4, 2006.
[5] Guozhong Chen,Xingzhao Liu "Wavelet-Based Despeckling SAR
Images Using Neighbouring Wavelet Cofficients" Proceedings of IEEE
2005.
[6] M.I.H.Bhuiyan,M Omair Ahmed "Wavelet-Based Spatially Adaptive
Method for Despeckling SAR Images". Proceedings of IEEE 2006.
[7] Sheng Guofang, Hu Xin, Jiao Licheng "SAR Image Denoising Based
on Data Fusion" Proceedings of IEEE 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 Inform
Theory,vol 41,pp.613-627,May 1995.
[10] H.S. Tan. (2001, October). "Denoising of
Noise Speckle in Radar Image"
[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, september2000.
[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] Ren Lu ,Xing Mengdao,Bao Zheng,Chen Haojun "Adaptive
Despeckling SAR Images Based on Space Correlation" Proceedings of
IEEE 2005.
[16] Siriporn Dachasilaruk,Yuttapong Rangsanser,Punya Thitimajshima
"Application of Multiscale Edge Detection to Speckle Reduction of SAR
Images".
[17] Anil K. Jain, "Fundamentals of Digital Image Processing" pp.245-
246,2004.
[1] Birgir Bjorn Saevarsson,Johannes R.Sveinsson and Jon Atli
Benediktsson "Combined Wavelet and Curvelet Denoising of SAR
Images" Proceedings of IEEE 2004.
[2] Guozhong Chen,Xingzhao Liu "Wavelet-Based Despeckling SAR
Images Using Neighbouring Wavelet Cofficients." Proceedings of IEEE
2005.
[3] Guozhong Chen,Xingzhao Liu "An Improved Wavelet-based Method
for SAR Images Denoising Using Data Fusion Technique". Proceedings
of IEEE 2006.
[4] Mario Mastriani "New Wavelet-based Superresolution Algorithm for
Speckle Reduction in SAR Images" IJCS volume 1 number 4, 2006.
[5] Guozhong Chen,Xingzhao Liu "Wavelet-Based Despeckling SAR
Images Using Neighbouring Wavelet Cofficients" Proceedings of IEEE
2005.
[6] M.I.H.Bhuiyan,M Omair Ahmed "Wavelet-Based Spatially Adaptive
Method for Despeckling SAR Images". Proceedings of IEEE 2006.
[7] Sheng Guofang, Hu Xin, Jiao Licheng "SAR Image Denoising Based
on Data Fusion" Proceedings of IEEE 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 Inform
Theory,vol 41,pp.613-627,May 1995.
[10] H.S. Tan. (2001, October). "Denoising of
Noise Speckle in Radar Image"
[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, september2000.
[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] Ren Lu ,Xing Mengdao,Bao Zheng,Chen Haojun "Adaptive
Despeckling SAR Images Based on Space Correlation" Proceedings of
IEEE 2005.
[16] Siriporn Dachasilaruk,Yuttapong Rangsanser,Punya Thitimajshima
"Application of Multiscale Edge Detection to Speckle Reduction of SAR
Images".
[17] Anil K. Jain, "Fundamentals of Digital Image Processing" pp.245-
246,2004.
@article{"International Journal of Information, Control and Computer Sciences:64644", author = "Syed Musharaf Ali and Muhammad Younus Javed and Naveed Sarfraz Khattak", title = "Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters", 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, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
", keywords = "Brute force thresholding, directional smoothing, direction dependent mask, undecimated wavelet transformation.", volume = "1", number = "7", pages = "2260-5", }
