航空斜视成像异速像移的实时恢复

Real-time restoration for aerial side-oblique images with different motion rates

提出了一种异速像移补偿算法,解决了航空相机斜视工作时成像靶面的异速像移补偿问题。当载机侧身飞行时,航空相机会处于斜视状态,成像靶面上会同时出现多个不同大小的像移量,生成复杂的运动模糊图像。提出的方法通过对异速像移产生机理的分析,根据像移量的不同将图像分成多个区;然后将各区图像继续细分到像素线来提高算法的运算效率;最后,用一维维纳滤波并行处理各像素线,将处理结果合并成结果图像。实验表明:运用本文算法的并行方案在GPU平台下17.11 ms内能恢复一帧2 048 bit×2 048 8 bit斜视模糊图像,恢复结果的峰值信噪比(PSNR)达到30.469,图像细节得到有效恢复。

Aerial cameras on the aircraft will work with a side-oblique angle, when alrcraft rues m 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.