Optics and Precision Engineering, Volume. 17, Issue 1, 225(2009)
Parallel restoration for motion-blurred aerial image
In order to improve the speed of restoration algorithm, a parallel Wiener filtering method based on Graphic Processing Unit(GPU)platform is presented to restore motion-blurred aerial image degraded in a deterministic way by motion or vibration. The shortages of the original algorithm using Wiener filtering and original PC run-time platform are introduced. On the basis of the new General Purpose GPU (GPGPU) technology, the original algorithm is divided into thousands of single algorithm threads to be computed in parallel. According to the special simultaneous operating mode of GPU hardware, a way in which the algorithm threads access the data on the GPU global memory is specially configured to improve the accessing speed, the algorithm efficiency by the special configuration can even be improved roughly 3 times that by original configuration. With the parallel computing ability of GPU, the new algorithm can restore 1 024×1 024 gray image in 8 ms per frame. The experimental result shows the new algorithm based on GPU reaches approximately 20 times that of original algorithm based on CPU of personal PC, which can completely be applied to the real time restoration of high resolution motion-blurred aerial image.
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LI Shi, ZHANG Bao, SUN Hui. Parallel restoration for motion-blurred aerial image[J]. Optics and Precision Engineering, 2009, 17(1): 225
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Received: Apr. 16, 2008
Accepted: --
Published Online: Oct. 9, 2009
The Author Email: Shi LI (brightlishi@gmail.com)
CSTR:32186.14.