相位恢复
算法
梯度下降
还原(数学)
光学
计算机科学
相(物质)
共轭梯度法
强度(物理)
数学
傅里叶变换
物理
人工智能
人工神经网络
数学分析
几何学
量子力学
出处
期刊:Applied optics
[The Optical Society]
日期:1982-08-01
卷期号:21 (15): 2758-2758
被引量:5208
摘要
Iterative algorithms for phase retrieval from intensity data are compared to gradient search methods. Both the problem of phase retrieval from two intensity measurements (in electron microscopy or wave front sensing) and the problem of phase retrieval from a single intensity measurement plus a non-negativity constraint (in astronomy) are considered, with emphasis on the latter. It is shown that both the error-reduction algorithm for the problem of a single intensity measurement and the Gerchberg-Saxton algorithm for the problem of two intensity measurements converge. The error-reduction algorithm is also shown to be closely related to the steepest-descent method. Other algorithms, including the input-output algorithm and the conjugate-gradient method, are shown to converge in practice much faster than the error-reduction algorithm. Examples are shown.
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