A comprehensive study on fast image deblurring techniques

Abstract

Image deblurring refers to procedures that attempt to reduce the blur amount in a blurry image and grant the degraded image an overall sharpened appearance to obtain a clearer image. The point spread function (PSF) is one of the essential factors that needed to be calculated, since it will be employed with different types of deblurring algorithms. In this paper, the authors studied various fast deblurring techniques like Richardson – Lucy and its optimized version, Van Cittert and its enhanced version, Landweber, Poisson Map, and Laplacian sharpening filters. Furthermore, altered optimized versions of Landweber and Poisson Map algorithms have been presented. The usage of the PSF in the deblurring algorithm is explained and a comparison between the optimized, the enhanced algorithms and Laplacian sharpening filters in terms of the number of mathematical operations, number of iterations employed, computation time, deblurring in case of noise existence, and the accuracy measurement using peak signal to noise ratio (PSNR) for each technique is conducted.