Gauss-Markov Model for Wavelet-Based SAR Image Despeckling

This letter presents synthetic aperture radar (SAR) image despeckling using dyadic wavelet transform. Maximum a posteriori (MAP) estimation is used to despeckle a SAR image in the wavelet domain. A wavelet transformed speckle-free image is approximated with a Gauss–Markov random field, and a Gaussian model is chosen to approximate speckle in the wavelet domain. A speckle-free wavelet coefficient is estimated with Bayesian inference using image and noise model parameters, which produce the highest evidence. The experimental results showed that the despeckling algorithm removes speckle noise in the homogeneous areas better than the state-of-the-art methods, which operate in the wavelet and image domain. The proposed method is very simple and computationally not demanding.

[1]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[2]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..

[3]  Aleksandra Pizurica,et al.  A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising , 2002, IEEE Trans. Image Process..

[4]  John Skilling,et al.  Data analysis : a Bayesian tutorial , 1996 .

[5]  Fabrizio Argenti,et al.  Speckle removal from SAR images in the undecimated wavelet domain , 2002, IEEE Trans. Geosci. Remote. Sens..

[6]  Jean-Marc Boucher,et al.  Multiscale MAP filtering of SAR images , 2001, IEEE Trans. Image Process..

[7]  Kannan Ramchandran,et al.  Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.

[8]  Alin Achim,et al.  SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling , 2003, IEEE Trans. Geosci. Remote. Sens..

[9]  R. Keith Raney,et al.  Spatial Considerations in SAR Speckle Simulation , 1988 .

[10]  Rama Chellappa,et al.  Texture synthesis and compression using Gaussian-Markov random field models , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  Il Kyu Eom,et al.  Wavelet-based denoising with nearly arbitrarily shaped windows , 2004, IEEE Signal Process. Lett..

[12]  Ken D. Sauer,et al.  A generalized Gaussian image model for edge-preserving MAP estimation , 1993, IEEE Trans. Image Process..

[13]  R. Raney,et al.  Spatial considerations in SAR speckle consideration , 1988 .

[14]  T. D. Bui,et al.  Multiwavelets denoising using neighboring coefficients , 2003, IEEE Signal Processing Letters.

[15]  Fawwaz T. Ulaby,et al.  SAR speckle reduction using wavelet denoising and Markov random field modeling , 2002, IEEE Trans. Geosci. Remote. Sens..

[16]  A. Lopes,et al.  A statistical and geometrical edge detector for SAR images , 1988 .

[17]  Dmitri Loguinov,et al.  Bayesian wavelet shrinkage with edge detection for SAR image despeckling , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Mihai Datcu,et al.  Model-based despeckling and information extraction from SAR images , 2000, IEEE Trans. Geosci. Remote. Sens..

[19]  M. Kazubek,et al.  Wavelet domain image denoising by thresholding and Wiener filtering , 2003, IEEE Signal Processing Letters.