SAR De-speckling using a Combination of Thresholding and MMSE/MAP Bayesian Estimation in Contourlet Transform Domain

Authors

Department of Electrical Engineering, University of Guilan, Rasht, Iran

Abstract

In the receiver antenna of SAR system electromagnetic waves backscattered from the target surface, add together coherently and random interference of these waves causes the speckle noise in reconstructed SAR images. Speckle may be modeled as a multiplicative noise which degrades the quality of SAR images. In this paper, we first present a review of low-complexity and high-speed despeakling algorithms which are developed based on thresholding and Bayesian estimation in non-subsampled contourlet transform (NSCT) domain. In usual thresholding methods when input amplitudes fall below a given threshold they are mapped to zero, however such amplitudes may contain useful information about image details. In order to simultaneously gain the low-complexity property of thresholding and high precision of Bayesian estimators, we then suggest a new thresholding method in which small-amplitude NSCT coefficients are estimated using LMMSE/MAP filters. The performance of despeckling filters is quantitatively evaluated on both simulated data and real SAR image using statistical indexes. The results illustrate the superior performance of the proposed algorithm in comparison with usual thresholding and Bayesian MMSE/MAP filters.

Keywords

References

[1] اهداف با حرکت غیریکنواخت در رادار دهانه ترکیبی معکوس»، مجله مهندسی برق دانشگاه تبریز، دوره 47، شماره 2، صفحه 400-391، تابستان 1396.
[2] F. Argenti, A. Lapini, T. Bianchi, and L. Alparone, “A tutorial on speckle reduction in synthetic aperture radar images,” IEEE Geoscience and Remote Sensing Magazine, vol. 1, no. 3, pp. 6-35, Sep. 2013.
[3] J. S. Lee, L. Jurkevich, P. Dewaele, P. Wambacq, and A. Oosterlinck, “Speckle filtering of synthetic aperture radar images: A review,” Remote Sensing Reviews, vol. 8, no. 4, pp. 313-340, 1994.
[4] D. T. Kuan, A. A. Sawchuk, T. C. Strand and P. Chavel, “Adaptive noise smoothing filter for images with signal dependent noise,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 7, no. 2, pp. 165-177, March 1985.
[5] M. Iqbal, J. Chen, W. Yang, P. Wang and B. Sun, “SAR image despeckling by selective 3D filtering of multiple compressive reconstruction images,” Progress in Electromagnetics Research, vol. 134, pp. 209-226, 2013.
[6] M. I. H. Bhuiyan, M. O. Ahmad, and M. N. S. Wamy, “Spatially adaptive wavelet-based method using the Cauchy prior for denoising the SAR images,” IEEE Trans. Circuits Syst. Video Technol., vol. 17, no. 4, pp. 500-507, April 2007.
[7] T. Bianchi, F. Argenti and L. Alparone, “Segmentation based MAP despeckling of SAR images in the undecimated wavelet domain,” IEEE Trans. Geo. And Remote Sensing, vol. 46, no. 9, pp. 2728-2742, Sep. 2008.
[8] F. Argenti, T. Bianchi, A. Lapini, and L. Alparone, “Fast MAP despeckling based on Laplacian-Gaussian modeling of wavelet coefficients,” IEEE Geosci. Remote Sensing Lett., vol. 9, no. 1, pp. 13-17, Jan. 2012.
[9] H. Chen, Y. Zhang, H. Wang, and C. Ding, “Stationary-wavelet based despeckling of SAR images using two-sided generalized gamma models,” IEEE Geosci. Remote Sensing Lett., vol. 9, no. 6, pp. 1061-1065, Nov. 2012.
[10] H. Rabbani, M. Vafadust, P. Abolmaesumi, and S. Gazor, “Speckle noise reduction of medical ultrasound images in complex wavelet domain using mixture priors,” IEEE Trans. Biomed. Eng., vol. 55, no. 9, pp. 2152-2160, Sept. 2008.
[11] S. G. Chang, B. Yu, and M. Vetterli, “Adaptive wavelet thresholding for image denoising and compression,” IEEE Trans. Image Process., vol. 9, no. 9, pp. 1532-1546, Sept. 2000.
[12] J. L. Starck, E. Candes, and D. Donoho, “The curvelet  transform for image denoising,” IEEE Trans. Image Process., vol. 11, no. 6, pp. 670-684, June 2002.
[13] منیره کوشش و غلامرضا اکبری‌زاده، «الگوریتم حذف Speckle با قابلیت حفظ لبه برای تصاویر سنجش از دور رادار روزنه ترکیبی با استفاده از تبدیل چند مقیاسه Curvelet و آستانه‌گذاری وفقی»، مجله مهندسی برق دانشگاه تبریز، دوره۴5، شماره 4، صفحه 161-153، زمستان 1394.
[14] M. Do and M. Vetterli, “The contourlet transform: An efficient directional multiresolution image representation,” IEEE Trans. Image Processing, vol.14, no.12, pp. 2091-2106, Dec. 2005.
[15] A. L. Da Cunha, J. Zhou, M. N. Do, “The nonsubsampled contourlet transform: theory, design, and application,” IEEE Trans. Image Process., vol. 15, no. 10, pp.3089-3101, Oct. 2006.
[16] D. X. Zhang, Q. W. Gao and X. P. Wu, “Bayesian-based speckle suppression for SAR image using contourlet transform,” Journal of electronic science and technology of china, vol. 6, no. 1, pp. 79-82, March 2008.
[17] F. Argenti, T. Bianchi, G. M. Di Scarfizzi, and L. Alparone, “LMMSE and MAP estimators for reduction of multiplicative noise in the nonsubsampled contourlet domain,” Elsevier Signal Process., vol. 89, no. 10, pp. 1891-1901, Oct. 2009.
[18] J. J. J. Babu, and G. F. Sudha,  “Non-subsampled contourlet transform based image denoising in ultrasound thyroid images using adaptive binary morphological operations,” IET Computer Vision,  vol. 8, no. 6, pp. 718-728, Dec. 2014.
[19] A. Rajshree, D. Venkataprasad, T. Joel and R. Sivakumar, "Comparative performance analysis of speckle reduction using curvelet and contourlet transform for medical images", Middle-East Journal of Scientific Research, vol. 24, pp. 88-95, 2016.
[20] D. D.-Y. Po and M. N. Do, “Directional multiscale modeling of images using the contourlet transform,” IEEE Trans. Image Process., vol. 15, no. 6, pp. 1610-1620, June 2006.
[21] F. Argenti, T. Bianchi, and L. Alparone, “Multiresolution MAP despeckling of SAR images based on locally adaptive generalized Gaussian pdf modeling,” IEEE Trans. Image Process., vol. 15, no. 11, pp. 3385-3399, Nov. 2006.
[22] S. G. Dellepiane and E. Angiati, “Quality assessment of despeckled SAR images,” IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens., vol. 7, no. 2, pp. 691-707, Sept. 2014.
[23] R. Touzi, “A review of speckle filtering in the context of estimation theory,” IEEE Trans. Geo. And Remote Sensing, vol. 40, no. 11, pp. 2392-2404, Nov. 2002.
[24] R. Touzi, “A review of speckle filtering in the context of estimation theory,” IEEE Trans. Geo. And Remote Sensing, vol. 40, no. 11, pp. 2392-2404, Nov. 2002.

Files

Share

How to cite

Statistics