Algorithm for the Removing Uniformed Motion Blur

Motion deblurring is one of the basic problems in the field of image processing. This paper summarizes the mathematical basis of the previous work and presents a deblurring method that can improve the estimation of the motion blur kernel and obtain a better result than the traditional methods. Experiments show the motion blur kernel loses some important and useful properties during the estimation of the kernel which may cause a bad estimation and increase the ringing artifacts. Considering that the kernel is provided by the motion of the imaging sensor during the exposure and that the kernel shows the trace of the motion, this paper ensures the physical meaning of the kernel such as the continuity and the center of the kernel during the iterative process. By adding a post process to the estimation of the motion blur kernel, we remove some discrete points and make use of the centralization of the kernel in order to accurate the estimation. The experiment shows the existence of the post process improves the effect of the estimation of the kernel and provides a better result with the clear edges.