24 November 2014 GPU-based parallel optimization implement of phase diversity
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Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 930137 (2014) https://doi.org/10.1117/12.2073135
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract
Phase diversity (PD) can not only be used as wavefront sensor but also as image post processing technique. However, its computations have been perceived as being too burdensome and it is difficult to achieve its real time application on a PC platform. In this paper, we carried out parallel analysis on the algorithm and task assignments on the heterogeneous platform of CPU-GPU, and then implement parallel programing optimization on GPUs. The optimization strategies of the cost function on GPU are introduced. The process of OTF is improved to make the amount of calcuation reduced by 11% compared to the original method. In order to demonstrate the speedup of PD, two images, 128x128 pixels and 256x256 pixels in dimension, are tested on CPU platform and CPU/GPU heterogeneous platform respectively. The results show the time costs have the improvenments of 13x and 28x for the implementation of PD based on GPU in contrast with that based on CPU.
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Quan Zhang, Hua Bao, Changhui Rao, Zhenming Peng, "GPU-based parallel optimization implement of phase diversity", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930137 (24 November 2014); doi: 10.1117/12.2073135; https://doi.org/10.1117/12.2073135
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