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This work deals with unsupervised image deblurring. We present a newdeblurring procedure on images provided by low-resolution synthetic apertureradar (SAR) or simply by multimedia in presence of multiplicative (speckle) oradditive noise, respectively. The method we propose is defined as a two-stepprocess. First, we use an original technique for noise reduction in waveletdomain. Then, the learning of a Kohonen self-organizing map (SOM) is performeddirectly on the denoised image to take out it the blur. This technique has beensuccessfully applied to real SAR images, and the simulation results arepresented to demonstrate the effectiveness of the proposed algorithms.

Denoising based on wavelets and deblurring via self-organizing map for Synthetic Aperture Radar images