Real-time restoration algorithm based on one-dimensional Wiener filters for different rates of image motion blur

摘要

To eliminate side-oblique image motion, a fast image al-ngorithm is proposed for implementation on aerial camera systems.nWhen an aerial camera works at a side-oblique angle, much parallelnimage motion with different rates will occur on the focal plane arraynsimultaneously. Through analysis of how different rates of parallelnimage motion blur are generated and the relationship between im-nage motion and the field of view (FOV) angle in side-oblique situa-ntions, the entire blurred image can be segmented into many slicesnby their different rates of image motion. To be computed quickly, thenslices are divided into pixel lines continuously, and then a specificnparallel computing scheme is presented using 1-D Wiener filters tonrestore all the pixel lines. With all the resulting pixel lines combined,nthe restoration image comes into being. The experiment resultsnshow that the proposed algorithm can effectively restore the detailsnof side-oblique blurred images. The peak signal-to-noise ration(PSNR) of the restored image can reach 31.426. With the help of thenparallel computing capability of a graphics processing unit (GPU),nthe proposed algorithm can restore a 2048u00012048 8-bit blurred im-nage in 17 ms, realizing real-time restoration.