Non-uniform image deblurring using an optical computing system

Removing non-uniform blur caused by camera shaking is troublesome because of its high computational cost. We analyze the efficiency bottlenecks of a non-uniform deblurring algorithm and propose an efficient optical computation deblurring framework that implements the time-consuming and repeatedly required modules, i.e., non-uniform convolution and perspective warping, by light transportation. Specifically, the non-uniform convolution and perspective warping are optically computed by a hybrid system that is composed of an off-the-shelf projector and a camera mounted on a programmable motion platform. Benefitting from the high speed and parallelism of optical computation, our system has the potential to accelerate existing non-uniform motion deblurring algorithms significantly. To validate the effectiveness of the proposed approach, we also develop a prototype system that is incorporated into an iterative deblurring framework to effectively address the image blur of planar scenes that is caused by 3D camera rotation around the x-, y- and z-axes. The results show that the proposed approach has a high efficiency while obtaining a promising accuracy and has a high generalizability to more complex camera motions. (C) 2013 Published by Elsevier Ltd.