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Speckle reduction is a key step in several SAR image processing procedures. In this paper, a new despeckling technique based on the "nonlocal" denoising filter BM3D [1] is presented. The filter has been modified in order to take into account SAR image characteristics. The experimental results, conducted on both synthetic and real SAR images, confirm the potential of the proposed approach.

In this work we propose a modified version of the BM3D algorithm recently introduced by Dabov et al. [1] for the denoising of images corrupted by additive white Gaussian noise. The original technique performs a multipoint filtering, where the nonlocal approach is combined with the wavelet shrinkage of a 3D cube composed by similar patches collected by means of block-matching. Our improvement concerns the thresholding of wavelet coefficients, which are subject to a different shrinkage depending on their level of sparsity. The modified algorithm is more robust with respect to block matching errors, especially when noise is high, as proved by experimental results on a large set of natural images. ©2010 IEEE

We propose a new framework for the quantitative assessment of SAR despeckling techniques, based on physical-level simulation of SAR images corresponding to canonical scenes. Thanks to the simulator, we can generate multiple SAR images of the same scene which differ only in the speckle content, and, hence, a true multilook SAR image, with an arbitrarily large number of looks, to use as "speckle-free" reference. Based on this concept, we select a small set of canonical scenes and, for each of them, a suitable set of objective measures which account for speckle suppression and image feature preservation. We gain insight into the system reliability by comparing the indications it gives for some sample despeckling filters with those obtained by expert visual inspection of the filtered images.Index Terms-Synthetic aperture radar (SAR), speckle reduction, quality assessment.