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Sub-Millisecond Phase Retrieval for Phase-Diversity Wavefront Sensor
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DOI：10.3390/s20174877.png)
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Abstract
En 中文
We propose a convolutional neural network (CNN) based method, namely phase diversity convolutional neural network (PD-CNN) for the speed acceleration of phase-diversity wavefront sensing. The PD-CNN has achieved a state-of-the-art result, with the inference speed about0.5ms, while fusing the information of the focal and defocused intensity images. When compared to the traditional phase diversity (PD) algorithms, the PD-CNN is a light-weight model without complicated iterative transformation and optimization process. Experiments have been done to demonstrate the accuracy and speed of the proposed approach.
Keywords:
phase diversity
convolutional nerual network
real time
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