Tracking Compensation in Computational Ghost Imaging of Moving Objects

Computational ghost imaging (CGI) captures images via the correlation between a set of illumination patterns and the transmitted/reflected signal of an object. It has been widely studied in many fields and has advanced from experimental verification to practical applications. However, there will be some motion blur in the results when a moving object is imaged with an insufficiently fast detector. To eliminate this blurring, we present here a tracking compensation method for CGI, in which a series of patterns illuminate the object according to the motion of the object, and the signal intensity is collected synchronously by the bucket detector. The principle of this compensation for moving and rotating objects is explained in detail. Both simulation and experimental results show that this method can effectively eliminate the motion blur and provide high quality reconstruction, outperforming conventional CGI, broad potential applications in object tracking, remote sensing and real-time imaging.