It is observed that, in the total variation model for image deblurring, if the regularisation term simply involves the first-order difference, details cannot be satisfactorily restored in a deblurred image. A weighted difference as the total variation regularisation term is considered, and the related half-quadratic model is solved to obtain a deblurring algorithm for saving more details and highlighting the edges of an image. The effectiveness of the proposed algorithm is tested by deblurring experiments.

The restoration quality of a motion-blurred image is highly dependent on the estimation accuracy of the motion blurring parameter. This manuscript presents a novel and precise method for estimation of the motion blurring length, wherein the ringing artifact amount of a deblurred image is measured by energy proportion contained in appropriate frequency bands, and a blurring length with minimum ringing artifact amount is taken as the optimal estimation of the true blurring length. Experimental results show good performance of the proposed algorithm in motion blurring length estimation.