Presentation + Paper
6 September 2019 Measuring the Fried parameter of transmissive phase screens using digital-holographic detection
Author Affiliations +
Abstract
This paper makes use of digital-holographic detection in the off-axis image plane recording geometry to determine the Fried parameter of transmissive phase screens. Digital-holographic detection, in practice, provides us with an estimate of the complex-optical field (i.e., both the amplitude and wrapped phase); thus, we can use this estimate for determining the Fried parameter of transmissive phase screens, especially when the resulting aberrations follow Kolmogorov statistics. As such, this paper uses two experimental setups and Lexitek phase plates, which make use of Kolmogorov statistics to create aberrations with a prescribed Fried parameter. In both experimental setups, we place the Lexitek phase plates under test near the single-receiver lens of our digital-holographic system and assume isoplanatic conditions. In the first experimental setup, we uniformly illuminate a chrome-on-glass bar chart backed by Labsphere Spectralon®. We then use digital-holographic detection and an image-sharpening algorithm to indirectly measure the aberrations and determine the Fried parameter. In the second experimental setup, we send a collimated beam through the Lexitek phase plates. We then use digital-holographic detection to directly measure the aberrations and determine the Fried parameter. The results show that the first experimental setup overestimates the prescribed Fried parameter by 20%-60%, whereas the second experimental setup produces less variability with estimates of ±20% of the prescribed Fried parameter.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel Horst, Cameron J. Radosevich, Casey J. Pellizzari, and Mark F. Spencer "Measuring the Fried parameter of transmissive phase screens using digital-holographic detection", Proc. SPIE 11135, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2019, 111350D (6 September 2019); https://doi.org/10.1117/12.2529680
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Imaging systems

Reconstruction algorithms

Statistical analysis

Digital recording

Model-based design

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