Aerial cameras on the aircraft will work with a side-oblique angle,when aircraft flies in a steep state,and many image motions with different rates occur on the focal plane array simultaneously.To compensate the different rates of image motion,an image algorithm is presented to improve the quality of blurred motion images in the aerial camera system.On the basis of the mechanism of the image motion with different rates generated in side-oblique situation,the entire blurred image is segmented into many slices by their different motion rates.Then,the slices are divided into pixel lines continuously to improve the computing speed,and a specific parallel computing scheme with 1D Wiener filters is utilized to restore all the pixel lines.Finally,a restored image is obtained by processed pixel lines combined together.The experimental results show that the proposed parallel computing algorithm can restore a blurred image of 2 048 bit×2 048 bit in 17.11 ms,with the help of the parallel computing capability of a GPU,and can offer good image details with a Peak Signal Noise Ratio (PSNR) of 30.469.