Registration Based Non-uniform Motion Deblurring

This paper proposes an algorithm which uses image registration to estimate a non-uniform motion blur point spread function (PSF) caused by camera shake. Our study is based on a motion blur model which models blur effects of camera shakes using a set of planar perspective projections (i.e., homographies). This representation can fully describe motions of camera shakes in 3D which cause non-uniform motion blurs. We transform the non-uniform PSF estimation problem into a set of image registration problems which estimate homographies of the motion blur model one-by-one through the Lucas-Kanade algorithm. We demonstrate the performance of our algorithm using both synthetic and real world examples. We also discuss the effectiveness and limitations of our algorithm for non-uniform deblurring.