  This work deals with unsupervised image deblurring. We present a new
deblurring procedure on images provided by low-resolution synthetic aperture
radar (SAR) or simply by multimedia in presence of multiplicative (speckle) or
additive noise, respectively. The method we propose is defined as a two-step
process. First, we use an original technique for noise reduction in wavelet
domain. Then, the learning of a Kohonen self-organizing map (SOM) is performed
directly on the denoised image to take out it the blur. This technique has been
successfully applied to real SAR images, and the simulation results are
presented to demonstrate the effectiveness of the proposed algorithms.
