
Proceedings Paper
Fast phase-only hologram calculation with a shared phase mask optimized from an image dictionaryFormat | Member Price | Non-Member Price |
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Paper Abstract
A common phase-type spatial light modulator (SLM) can only modulate the phase part of a complex-amplitude hologram calculated from an object image. To calculate a phase-only hologram, iterative methods such as the Gerchberg–Saxton algorithm can be employed. However, one-step non-iterative phase-only hologram calculation is more favorable for real-time applications. This paper proposes a novel scheme to optimize a shared phase mask from a set of training images. Then a phase-only hologram can be simply calculated by phase truncation after any given object image similar to the training samples is multiplied with the shared mask and Fresnel diffracted. The speckle noise in the reconstructed images can be significantly suppressed if our optimized phase mask is used instead of a conventional random phase mask.
Paper Details
Date Published: 12 March 2020
PDF: 7 pages
Proc. SPIE 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 114340F (12 March 2020); doi: 10.1117/12.2542496
Published in SPIE Proceedings Vol. 11434:
2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Juan Liu; Baohua Jia; Xincheng Yao; Yongtian Wang; Takanori Nomura, Editor(s)
PDF: 7 pages
Proc. SPIE 11434, 2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments, 114340F (12 March 2020); doi: 10.1117/12.2542496
Show Author Affiliations
Shuming Jiao, Shenzhen Univ. (China)
Yang Gao, Shenzhen Univ. (China)
Ting Lei, Shenzhen Univ. (China)
Yang Gao, Shenzhen Univ. (China)
Ting Lei, Shenzhen Univ. (China)
Published in SPIE Proceedings Vol. 11434:
2019 International Conference on Optical Instruments and Technology: Optical Systems and Modern Optoelectronic Instruments
Juan Liu; Baohua Jia; Xincheng Yao; Yongtian Wang; Takanori Nomura, Editor(s)
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