NDLI: Optical phase retrieval with the image of intensity in the focal plane based on the convolutional neural networks

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Optical phase retrieval with the image of intensity in the focal plane based on the convolutional neural networks

Content Provider	Scilit
Author	Dzyuba, A. P.
Copyright Year	2019
Description	Journal: Journal of Physics: Conference Series One of the most important factors for improving the resolution of optical systems is to compensate for the aberrations (distortions) of the wave front. As a rule, whether special measuring devices (wavefront sensors) are used for such compensation or adaptive mirrors that perform iterative correction of the wavefront. However, often (for reasons of compactness or weight reduction), it is not possible to use the special equipment for measuring aberrations. To obtain certain information on the wave front, one can use the measured point spread function (PSF) or the intensity pattern in the focal plane. Methods of processing two PSFs (focal and nonfocal) with the help of neural networks are known. In this paper, we investigate the possibility of recognizing the wave front from a single intensity pattern in the focal plane. The technology of deep machine learning - convolutional neural network is chosen as the way for implementation. The idea of this technology lies in the alternation of convolutional and subsampling layers, for the purpose of efficient image recognition. Such approach will allow to optimize the process of compensation of optical system aberrations and to reduce the amount of required input data.
Related Links	https://iopscience.iop.org/article/10.1088/1742-6596/1368/2/022055/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/1368/2/022055
Journal	Journal of Physics: Conference Series
Issue Number	2
Volume Number	1368
Language	English
Publisher	IOP Publishing
Publisher Date	2019-11-01
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Focal Plane Wave Front Convolutional Neural Network
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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