A blind restoration system of blurred and noisy numerical images

This paper presents a totally blind restoration system of blurred and noisy images. It includes two processing modules, one for identifying the blur PSF and another for blind image restoration. The blur PSF identification and estimation is achieved using the generalized cross-validation criterion and a smoothness constraint on the image. The deblurring step is based on a Tikhonov-Miller regularization technique. Simulation results show that this system yields rather good results on various kind of images with low signal-to-noise ratio. It is quite effective in restoring severely blurred and noise corrupted images, without prior knowledge of either the noise or image characteristics. It can also discriminate between blurred and unblurred images.