Despeckling of Synthetic Aperture Radar Images Using Monte Carlo Texture Likelihood Sampling

Speckle noise is found in synthetic aperture radar (SAR) images and can affect visualization and analysis. A novel stochastic texture-based algorithm is proposed to suppress speckle noise while preserving the underlying structural and texture detail. Based on a sorted local texture model and a Fisher-Tippett logarithmic-space speckle distribution model, a Monte Carlo texture likelihood sampling strategy is proposed to estimate the true signal. The algorithm is compared to six other classic and state-of-the-art despeckling techniques. The comparison is performed both on synthetic noisy images added and on actual SAR images. Using peak signal-to-noise ratio, contrast-to-noise ratio, and structural similarity index as image quality metrics, the proposed algorithm shows strong despeckling performance when compared to existing despeckling algorithms.

[1]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  J. Fujimoto,et al.  Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter. , 2004, Optics letters.

[3]  D. Kaplan,et al.  On the statistical characteristics of log-compressed Rayleigh signals: theoretical formulation and experimental results , 1993 .

[4]  Alexandre Jouan,et al.  Speckle filtering of SAR images: a comparative study between complex-wavelet-based and standard filters , 1997, Optics & Photonics.

[5]  Zhenghao Shi,et al.  A comparison of digital speckle filters , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[6]  Robert A. Shuchman,et al.  Textural Analysis And Real-Time Classification of Sea-Ice Types Using Digital SAR Data , 1984, IEEE Transactions on Geoscience and Remote Sensing.

[7]  John C. Curlander,et al.  Synthetic Aperture Radar: Systems and Signal Processing , 1991 .

[8]  E. Nezry,et al.  Structure detection and statistical adaptive speckle filtering in SAR images , 1993 .

[9]  Scott T. Acton,et al.  Speckle reducing anisotropic diffusion , 2002, IEEE Trans. Image Process..

[10]  Leen-Kiat Soh,et al.  Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices , 1999, IEEE Trans. Geosci. Remote. Sens..

[11]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Ming-Hui Chen.  Importance-Weighted Marginal Bayesian Posterior Density Estimation , 1994 .

[13]  Laurent Ferro-Famil,et al.  Nonstationary Spatial Texture Estimation Applied to Adaptive Speckle Reduction of SAR Data , 2006, IEEE Geoscience and Remote Sensing Letters.

[14]  Bibo Lu,et al.  Speckle Reduction with Multiresolution Bilateral Filtering for SAR Image , 2010, 2010 International Conference on Machine Vision and Human-machine Interface.

[15]  Victor S. Frost,et al.  A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  David A. Clausi,et al.  Sorted random projections for robust rotation-invariant texture classification , 2012, Pattern Recognit..

[17]  Anil K. Jain,et al.  Unsupervised texture segmentation using Gabor filters , 1990, 1990 IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings.

[18]  Fawwaz T. Ulaby,et al.  Statistical properties of logarithmically transformed speckle , 2002, IEEE Trans. Geosci. Remote. Sens..

[19]  Josiane Zerubia,et al.  Modeling SAR images with a generalization of the Rayleigh distribution , 2004, IEEE Transactions on Image Processing.

[20]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[21]  Heng-Chao Li,et al.  Texture-Preserving Despeckling of SAR Images Using Evidence Framework , 2007, IEEE Geoscience and Remote Sensing Letters.

[22]  Paul Fieguth,et al.  Statistical Image Processing and Multidimensional Modeling , 2010 .

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

[24]  S. Intajag,et al.  Speckle Reduction Using Fuzzy Morphological Anisotropic Diffusion , 2005, 2005 5th International Conference on Information Communications & Signal Processing.

[25]  Daniel N. Held,et al.  Comparison of Several Techniques to Obtain Multiple-Look SAR Imagery , 1983, IEEE Transactions on Geoscience and Remote Sensing.

[26]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[27]  Tong Fang,et al.  Ultrasound-Specific Segmentation via Decorrelation and Statistical Region-Based Active Contours , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[28]  Alessandro Foi,et al.  Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.