Abstract
We propose a novel algorithm for the de-speckling of SAR images which exploits a priori statistical information from both the spatial and wavelet domains. In the spatial domain, we apply the Method-of-Log-Cumulants (MoLC), which is based on Mellin transform, in order to locally estimate parameters corresponding to an assumed Generalized Gaussian Rayleigh (GGR) model for the image. We then compute classical cumulants for the image and speckle models and relate them into their wavelet domain counterparts. Using wavelet cumulants, we separately derive parameters corresponding to an assumed generalized Gaussian (GG) model for the image and noise wavelet coefficients. Finally, we feed the resulting parameters into a Bayesian maximum a priori (MAP) estimator, which is applied to the wavelet coefficients of the log-transformed SAR image. Our proposed method outperforms several recently proposed de-speckling techniques both visually and in terms of different objective measures.
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Xie, H., Pierce, L., Ulaby, F.: SAR speckle reduction using wavelet denoising and Markov random field modeling. IEEE Trans. Geosci. Remote Sensing 40, 2196–2212 (2002)
Solb ø, S., Eltoft, T.: Homomorphic Wavelet-Based Statistical De-speckling of SAR Images. IEEE Trans. on Geosci. and Remote Sensing 42(4) (April 2004)
Argenti, F., Rovai, N., Alparone, L.: De-speckling SAR Images In The Undecimated Wavelet Domin: A MAP Approach. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, Proceedings, vol. 4, pp. 541–544 (March 2005)
Achim, A., Kuruoglu, E., Zerubia, J.: SAR image filtering based on the heavy-tailed Rayleigh model. IEEE Transactions on Image Processing 15(9), 2686–2693 (2006)
Moser, G., Zerubia, J., Serpico, S.B.: SAR amplitude probability density function estimation based on a Generalized Gaussian scattering model. Image Processing, IEEE Transactions on 15(6), 1429–1442 (2006)
Nicolas, J.M.: Introduction aux statistiques de deuxième espèce: applications des logmoments et des log-cumulants à l’analyse des lois d’images radar. Traitement du Signal 19, 139–167 (2002)
Nason, G.P., Silverman, B.W.: The stationary wavelet transform and some statistical applications, Univ. Bristol, Bristol, U.K., Tech. Rep. BS8 1Tw (1995)
Simoncelli, E., Adelson, E.: Noise removal via Bayesian wavelet coring. In: Third Int’l Conf on Image Proc, vol. I, pp. 379–382 (September 1996)
Achim, A., Kuruoglu, E.: Image denoising using bivariate α stable distributions in the complex wavelet domain. IEEE Signal Processing Letters 12(1) (January 2005)
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© 2007 Springer-Verlag Berlin Heidelberg
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Lim, K., Canagarajah, N., Achim, A. (2007). SAR Speckle Mitigation by Fusing Statistical Information from Spatial and Wavelet Domains. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_95
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DOI: https://doi.org/10.1007/978-3-540-77255-2_95
Publisher Name: Springer, Berlin, Heidelberg
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