Convolutional neural network-based spectrum reconstruction solver for channeled spectropolarimeter
文献类型：期刊论文
| 作者 | Huang, Chan3; Wu, Su2; Chang, Yuyang2; Fang, Yuwei3; Zou, Zhiyong1; Qiu, Huaili3 |
| 刊名 | OPTICS EXPRESS
 |
| 出版日期 | 2022-03-28 |
| 卷号 | 30 |
| ISSN号 | 1094-4087 |
| DOI | 10.1364/OE.454127 |
| 通讯作者 | Zou, Zhiyong(zyzou@ie.ah.cn) |
| 英文摘要 | Channeled spectropolarimetry is a snapshot technique for measuring the spectra of Stokes parameters of light by demodulating the measured spectrum. As an indispensable part of the channeled spectropolarimeter, the spectrometer module is far from being perfect to reflect the real modulation spectrum, which further reduces the polarimetric reconstruction accuracy of the channeled spectropolarimeter. Since the modulation spectrum is composed of many continuous narrow-band spectra with high frequency, it is a challenging work to reconstruct it effectively by existing methods. To alleviate this issue, a convolutional neural network (CNN)-based spectral reconstruction solver is proposed for channeled spectropolarimeter. The key idea of the proposed method is to first preprocess the measured spectra using existing traditional methods, so that the preprocessed spectra contain more spectral features of the real spectra, and then these spectral features are employed to train a CNN to learn a map from the preprocessed spectra to the real spectra, so as to further improve the reconstruction quality of the preprocessed spectra. A series of simulation experiments and real experiments were carried out to verify the effect of the proposed method. In simulation experiments, we investigated the spectral reconstruction accuracy and robustness of the proposed method on three synthetic datasets and evaluate the effect of the proposed method on the demodulation results obtained by the Fourier reconstruction method. In real experiments, system matrices are constructed by using measured spectra and reconstructed spectra respectively, and the spectra of Stokes parameters of incident light are estimated by the linear operator method. Several other advanced demodulation methods are also used to demodulate the measured spectrum in both simulation and real experiments. The results show that compared with other methods, the accuracy of the demodulation results can be much more improved by employing the CNN-based solver to reconstruct the measured spectrum. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement |
| WOS关键词 | CORRECTION ALGORITHM ; POLARIZATION ; ERRORS ; POLARIMETRY ; MODULATION ; ALIGNMENT |
| 资助项目 | HFIPS Director's Fund[YZJJ2022QN12] ; Institute of Energy, Hefei Comprehensive National Science Center[21KZS205] |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000781665200013 |
| 出版者 | Optica Publishing Group |
| 资助机构 | HFIPS Director's Fund ; Institute of Energy, Hefei Comprehensive National Science Center |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/128613]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Zou, Zhiyong |
| 作者单位 | 1.Hefei Comprehens Natl Sci Ctr, Inst Energy, Hefei 230601, Anhui, Peoples R China 2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei 230031, Anhui, Peoples R China 3.Hefei Univ Technol, Sch Phys, Dept Opt Engn, Hefei 230601, Anhui, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Chan,Wu, Su,Chang, Yuyang,et al. Convolutional neural network-based spectrum reconstruction solver for channeled spectropolarimeter[J]. OPTICS EXPRESS,2022,30. |
| APA | Huang, Chan,Wu, Su,Chang, Yuyang,Fang, Yuwei,Zou, Zhiyong,&Qiu, Huaili.(2022).Convolutional neural network-based spectrum reconstruction solver for channeled spectropolarimeter.OPTICS EXPRESS,30. |
| MLA | Huang, Chan,et al."Convolutional neural network-based spectrum reconstruction solver for channeled spectropolarimeter".OPTICS EXPRESS 30(2022). |
入库方式： OAI收割
来源：合肥物质科学研究院
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