GS Iterative Phase Retrieval Algorithm Based on Fusion of Spatial Phase Gradient Descent and Frequency Domain Amplitude Linear Weighting

2022 IEEE 7th Optoelectronics Global Conference (OGC)(2022)

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摘要
For the problems of slow convergence and low accuracy of the traditional linear weighted GS iterative phase retrieval algorithm, a GS iterative phase retrieval algorithm based on the fusion of spatial phase gradient descent and frequency domain amplitude linear weighting is proposed. By zero-padding the image, and then applying phase gradient descent in each iteration of the space domain, the algorithm invokes linear weighting in the frequency domain space, thereby avoiding iterative stagnation while ensuring the convergence speed and improving the accuracy of phase retrieval.
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关键词
phase retrieval,Gerchberg–Saxton algorithm,phase gradient descent,amplitude Linear Weighting,zero-padding
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