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题名:
Optical surface measurement using phase retrieval hybrid algorithm based on diffraction angular spectrum theory
作者: Feng, Liang1,2; Zeng, Zhi-Ge1; Wu, Yong-Qian1
出版日期: 2013
会议名称: Proceedings of SPIE: International Symposium on Photoelectronic Detection and Imaging 2013: Micro/Nano Optical Imaging Technologies and Applications
会议日期: 2013
学科分类: Algorithms - Conjugate gradient method - Diffraction - Spectrum analysis - Surface measurement
DOI: 10.1117/12.2035185
中文摘要: In order to test the high dynamic range error beyond one wavelength after the rough polish process, we design a phase retrieval hybrid algorithm based on diffraction angular spectrum theory. Phase retrieval is a wave front sensing method that uses the intensity distribution to reconstruct the phase distribution of optical field. Phase retrieval is established on the model of diffractive propagation and approach the real intensity distribution gradually. In this paper, we introduce the basic principle and challenges of optical surface measurement using phase retrieval, then discuss the major parts of phase retrieval: diffractive propagation and hybrid algorithm. The angular spectrum theory describes the diffractive propagation in the frequency domain instead of spatial domain, which simplifies the computation greatly. Through the theoretical analysis, the angular spectrum in discrete form is more effective when the high frequency part values less and the diffractive distance isn't far. The phase retrieval hybrid algorithm derives from modified GS algorithm and conjugate gradient method, aiming to solve the problem of phase wrapping caused by the high dynamic range error. In the algorithm, phase distribution is described by Zernike polynomials and the coefficients of Zernike polynomials are optimized by the hybrid algorithm. Simulation results show that the retrieved phase distribution and real phase distribution are quite contiguous for the high dynamic range error beyond λ. © 2013 SPIE.
英文摘要: In order to test the high dynamic range error beyond one wavelength after the rough polish process, we design a phase retrieval hybrid algorithm based on diffraction angular spectrum theory. Phase retrieval is a wave front sensing method that uses the intensity distribution to reconstruct the phase distribution of optical field. Phase retrieval is established on the model of diffractive propagation and approach the real intensity distribution gradually. In this paper, we introduce the basic principle and challenges of optical surface measurement using phase retrieval, then discuss the major parts of phase retrieval: diffractive propagation and hybrid algorithm. The angular spectrum theory describes the diffractive propagation in the frequency domain instead of spatial domain, which simplifies the computation greatly. Through the theoretical analysis, the angular spectrum in discrete form is more effective when the high frequency part values less and the diffractive distance isn't far. The phase retrieval hybrid algorithm derives from modified GS algorithm and conjugate gradient method, aiming to solve the problem of phase wrapping caused by the high dynamic range error. In the algorithm, phase distribution is described by Zernike polynomials and the coefficients of Zernike polynomials are optimized by the hybrid algorithm. Simulation results show that the retrieved phase distribution and real phase distribution are quite contiguous for the high dynamic range error beyond λ. © 2013 SPIE.
收录类别: Ei
语种: 英语
卷号: 8911
ISSN号: 0277786X
文章类型: 会议论文
页码: 891111
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7599
Appears in Collections:先光中心_会议论文

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作者单位: 1. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
2. University of Chinese Academy of Sciences, Beijing, 100049, China

Recommended Citation:
Feng, Liang,Zeng, Zhi-Ge,Wu, Yong-Qian. Optical surface measurement using phase retrieval hybrid algorithm based on diffraction angular spectrum theory[C]. 见:Proceedings of SPIE: International Symposium on Photoelectronic Detection and Imaging 2013: Micro/Nano Optical Imaging Technologies and Applications. 2013.
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