在地基太阳观测中,光线在穿越大气层时会受到大气湍流的影响而导致图像扭曲、变形以致质量下降。为了消除或降 低大气湍流的影响,事后图像处理技术被用来获得高分辨力的太阳图像。基于斑点干涉法和斑点掩模的事后重建算 法可以获得高分辨力的图像,但由于计算复杂度高,难以满足实时性的要求。在讨论了算法原理的基础上, 使用CUDA并行计算架构实现了太阳斑点重建算法并行化。实验结果表明,在GPU环境下,一张TiO通 道2304 pixel×1984 pixel像素大小的图像,可以在70 s内完成重建,相比运行在CPU上的串行程序,加速比可达7以上。

In ground-based solar observation, when the light passes through atmosphere, it will be affected by atmospheric turbulence which will cause translation, distortion and blurring of the received image. In order to eliminate or reduce the effects of atmospheric turbulence, post-image processing technology was used to obtain high-resolution solar images. High-resolution image can be obtained by post-facto reconstruction algorithm based on the speckle interferometry and speckle masking. However, due to its complex calculation, the algorithm can not meet the requirement of real-time detection. On the basis of the principle of the algorithm, solar speckle image reconstruction algorithm has been parallelized by using CUDA parallel computing architecture in this research. The experimental results show that a 2304 pixel×1984 pixel image of TiO channel can be reconstructed within 70 s under GPU environment. Compared with the program running on CPU, the speed-up radio can up to 7.