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Phase diversity algorithm with high noise robust based on deep denoising convolutional neural network

文献类型：期刊论文

作者D.Q.Li; S.Y.Xu; D.Wang; D.J.Yan
刊名Optics Express
出版日期2019
卷号27期号:16页码:22846-22854
关键词Optics
ISSN号1094-4087
DOI10.1364/oe.27.022846
英文摘要The wave-front phase expanded on the Zernike polynomials is estimated from a pair of images by the use of a maximum-likelihood approach, the in-focus image and the defocus image, which contaminated by noise, will greatly reduce the solution accuracy of the phase diversity (PD) algorithm. In the study, we introduce the deep denoising convolutional neural networks (DnCNNs) into the image preprocessing of PD to denoise the in-focus image and defocus the image containing gaussian white noise to improve the robustness of PD to noise. The simulation results show that the composite PD algorithm with DnCNNs is better than the traditional PD algorithm in both RMSE of phase estimation and SSIM, and the mean of the RMSE of the phase estimation of the improved PD algorithm is reduced by 78.48%, 82.35%, 71.09% and 73.67% compared with the mean of the RMSE of the phase estimation of the traditional PD algorithm. The well-trained DnCNNs runs fast, which does not increase the running time of traditional PD algorithms, and the compound approach may be widely used in various domains, such as the measurements of intrinsic aberrations in optical systems and compensations for atmospheric turbulence. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/63274]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714		 D.Q.Li,S.Y.Xu,D.Wang,et al. Phase diversity algorithm with high noise robust based on deep denoising convolutional neural network[J]. Optics Express,2019,27(16):22846-22854.
APA D.Q.Li,S.Y.Xu,D.Wang,&D.J.Yan.(2019).Phase diversity algorithm with high noise robust based on deep denoising convolutional neural network.Optics Express,27(16),22846-22854.
MLA D.Q.Li,et al."Phase diversity algorithm with high noise robust based on deep denoising convolutional neural network".Optics Express 27.16(2019):22846-22854.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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