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Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform
Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform
A. Ray1 , B. Kartikeyan2 , S. Garg3

Section:Research Paper, Product Type: Journal Paper
Volume-4 , Issue-10 , Page no. 33-46, Oct-2016

Online published on Oct 28, 2016

Copyright © A. Ray, B. Kartikeyan, S. Garg . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 
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IEEE Style Citation: A. Ray, B. Kartikeyan, S. Garg, “Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform”, International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.33-46, 2016.

MLA Style Citation: A. Ray, B. Kartikeyan, S. Garg "Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform." International Journal of Computer Sciences and Engineering 4.10 (2016): 33-46.

APA Style Citation: A. Ray, B. Kartikeyan, S. Garg, (2016). Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform. International Journal of Computer Sciences and Engineering, 4(10), 33-46.
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Abstract :
Synthetic Aperture Radar(SAR) image filtering has been of interest since its inception. A variety of denoising filters for SAR images have been proposed in the recent years, which are targeted at removing the speckle noise to increase the contrast of the image, and make it useful for further image interpretation and applications. Of late, Wavelet based SAR data denoising techniques have been gaining popularity due to its space-frequency localization capability and the capacity to analyse the data at different scales. In this paper, we have attempted to derive an optimal approach for wavelet based SAR image filtering based on the quality criteria which takes into account not only the radiometric quality but also the geometric quality using point target data of actual Corner Reflector. Different orders of Daubechies wavelet coefficients have been used in the DWT(Discrete Wavelet Transform) based approach. In this study all aspects of an image quality have been taken into consideration such as the geometric fidelity and the radiometric quality, and using a simple heuristic soft thresholding criteria, optimal basis has been arrived at.
Key-Words / Index Term :
SAR, speckle, denoising, Wavelet based denoising, thresholding, decomposition, mother wavelets, radiometric resolution, geometric resolution, corner reflector.
References :
[1] F T Ulaby, R K Moore and A K Fung, �Microwave Remote Sensing Active and Passive�, Artech House, Vol-II, 1986.
[2] J Reeves, �Manual of Remote Sensing, American Society Of Photogrammetry�, First Edition, Vol-1, 1975.
[3] R K Raney, �Radar Fundamentals: Technical Perspective, Principles and Applications of Imaging Radar: Manual of Remote Sensing�, 3rd Edition, New York: Wiley Interscience, Vol- 2, pp (9-130), 1998.
[4] G V E R Harvy, �Speckle Statistics in Four-Look Synthetic Aperture Radar Imagery�, Optical Engineering, Vol-30 Issue-4, pp (375-381), 1991.
[5] J Bruniquel and A Lopes, �Multivariate Optimal Speckle Reduction in SAR Imagery�, International Journal of Remote Sensing, Vol-18, Nos-3, pp(603-627), 1997.
[6] J S Lee, �Speckle Suppression and Analysis for Synthetic Aperture Radar Images�, Optical Engineering, 25(5), pp(636-643), 1986.
[7] J S Lee, �Digital image enhancement and noise filtering by use of local statistics�, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol-2, pp(165-168), 1980.
[8] V S Frost, J A Stiles, K S Shanmugan, J C Holtzman, �A model for radar images and its application to adaptive digital filtering of multiplicative noise�, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol-4, pp(157-166), 1982.
[9] D T Kuan, A A Sawchuk, T C Strand, P Chavel, �Adaptive noise smoothing filter for images with signal dependant noise�, IEEE Transaction on PAMI-7, No-2, pp(165-177), 1985.
[10] A Baraldi, F Pannigiann, �A refined Gamma MAP SAR speckle filter with improved geometrical adaptivity�, IEEE Transactions on Geoscience and Remote Sensing, Vol-33, pp(1245-1257), 1995.
[11] S G Mallat, �Theory for Multiresolution Signal Decomposition: The Wavelet Representation�, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol-11, Issue-7, pp(674-693), 1989.
[12] F Argenti, L Alparone, �Speckle Removal from SAR Images in the Undecimated Wavelet Domain�, IEEE Transactions on Geoscience and Remote Sensing, Vol-40, pp( 2363-2374), 2002.
[13] L Gagnon, A Jouan, �Speckle filtering of SAR images - A comparative study between complex-wavelet based and standard filters�, SPIE Proceedings, Vol-3169, pp(80-91), 1997.
[14] Jia-Hua Hou, Xiang-Ming Liu, Cheng-Yi Xiong, He Xiang, �Speckle reduction algorithm for synthetic aperture radar images based on Bayesian Maximum a Posteriori estimation in wavelet domain�, Optical Engineering, 47_5_ 057004, pp(057004-1 � 057004-11), 2008.
[15] P U Fangling, X U Xin, �Wavelet-domain suppression of speckle in single-look SAR images�, Proceedings of SPIE Vol- 4552, doi:10.1117/12.441515, 2001.
[16] S Solbo, T Eltoft, �Homomorphic wavelet based statistical despeckling of SAR images�, IEEE Transactions on Geoscience and Remote Sensing, Vol-42, pp(711-721), 2004.
[17] Dusan Gleich, and Mihai Datchu, �Wavelet based SAR image despeckling and information extraction, using particle filter�, IEEE Transactions on Image Processing, Vol. 18, Issue-10, pp(2167-2184), 2009.
[18] S Parrilli, M Poderico, Vincenzo Angelino, C L Verdoliva, �A nonlocal SAR image denoising algorithm based on LMMSE wavelet shrinkage�, IEEE Transactions on Geoscience and Remote Sensing, Vol-50, Issue-2, pp(606-616), 2012.
[19] K Dabov, A Foi, V Katkovnik, K Egiazarian, �Image Denoising by Sparse 3D Transform-Domain Collaborative Filtering�, IEEE Transactions on Image Processing, Vol-16, (8), pp(2080-2095), 2007.
[20] H L Xie, E Pierce, F T Ulaby, �Statistical properties of logarithmically transformed speckle�, IEEE Transactions on Geoscience and Remote Sensing, Vol-40, pp(721-727), 2002.
[21] L Gagnon, �Wavelet Filtering of Speckle Noise - Some Numerical Results�, Vision Interface, Trois-Rivi�res, Canada,19-21, pp(336-343),1999.
[22] I Daubechies, �The wavelet transform time frequency localization and Signal Analysis�, IEEE Transactions on Information Theory, Vol-36, Issue-5, pp(961-1005),1990.
[23] D L Donoho, �Denoising by soft thresholding�, IEEE Transactions on Information Theory, Vol- 41, pp(613- 627), 1995.
[24] X P Zhang, M Desai, �Adaptive denoising based on SURE Risk�, IEEE Signal Processing Letters, Vol-5, Issue-10, pp. 265-267, 1998.
[25] Thierry Blu, Florian Luisier, �The SURE-LET Approach to Image Denoising�, IEEE Transactions on Image Processing, Vol-1, Issue-11, pp(2778-2786), 2007.
[26] S G Chang, B Yu, M Vetterli, �Adaptive Wavelet Thresholding for Image Denoising and Compression�, IEEE Transactions on Image Processing, Vol- 9, pp(1532-1546), 2000.
[27] H Xie, L E Pierce, F T Ulaby, �SAR Speckle reduction using wavelet denoising and Markov Random Field Modeling�, IEEE Transactions on Geoscience and Remote Sensing, Vol-40, No 10, pp(2196-2212), 2002.
[28] T Misra, S S Rana, N M Desai, D B Dave, RajeevJyoti, R K Arora, C V N Rao, B V Bakori, R Neelakantan, J G Vachchani, �Synthetic Aperture Radar Payload On-Board RISAT-1: Configuration, Technology and Performance�, Current Science (00113891) 104 (4), pp. (447-461), 2013,.
[29] SAC, RISAT-1-SAR Payload Detailed Design Review Document, Internal Document, SAC/RISAT/DDR/01/ 2009.
[30] Arundhati Misra, B Kartikeyan, S Garg, �Denoising Of SAR Imagery In The Wavelet Framework: Performance Analysis�, International Journal of Remote Sensing & Geoscience (IJRSG), Vol-3, Issue-2, ISSN No: 2319-3484, 2014.
[31] Arundhati Misra, B Kartikeyan, S Garg, �Towards Identifying Optimal Quality Indicators For Evaluating Denoising Algorithm Performance In SAR�, International Journal of Computer Science and Communication, Vol-7, No1, pp(1-10), 2016.
[32] Arundhati Ray and B Kartikeyan, �Denoising Techniques For Synthetic Aperture Radar Data � A Review�, International Journal of Computer Engineering and Technology , Vol-6, Issue-9, pp (01-11), 2015.
[33] V S Rathore & V S Kharsan, �Simulation of Hybrid Filter Model to Enhance the Quality of Noisy Images�, International Journal of Computer Sciences and Engineering, Vol-04, Issue-07, pp (18-23), July, 2016.