Abstract:

Image restoration is a deconvolution process, which is usually morbid. Blind deconvolution is one of the most common and challenging problems. Without priori knowledge on point spread function, the process is therefore more complex. To preserve the edge information of an image as well as its smoothness, we present a blind deconvolution model with a modified total variation regularization term. We also solve the model with split Bregman iteration algorithm. Fast Fourier transform and shrinkage formula are applied in numerical calculation to reduce its computational complexity. We apply the model to the processing for a blurry image and a greyscale image with noise and Gaussian blur in numerical experiment, and then obtain satisfactory results.

Key words: point spread function, fast Fourier transform, blind deconvolution')">blind deconvolution, split Bregman algorithm