Abstract
A computer generated kinoform combined with error diffusion and the dynamic random phase is presented. In order to compensate the error generated in the reconstructed image from the phase only hologram, the Floyd-Steinberg error diffusion technique is employed. The error can be diffused to the neighboring pixels in this method. And sequential kinoforms are generated by adding dynamic phase factor into the object domain to reduce the speckle noise. The results show that the kinoform can be achieved correctly and the representation quality of the reconstructed image can be improved compared with that obtained from the original kinoform.
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Acknowledgment
This work was supported by the Scientific and Technological Projects of Shenzhen (No. JCYJ20190808093001772), Guangdong Province higher vocational colleges & schools Pearl River scholar funded scheme (2016), Project of Shenzhen Science and Technology Innovation Committee (JCYJ20170817114522834), Research platform and project of Department of Education of Guangdong Province (2019GGCZX009), Engineering Applications of Artificial Intelligence Technology Laboratory (No. PT201701), Provincial Natural Science Foundation of Guangdong (No. 2017A030313337).
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Cao, X., Guan, M., Xia, L., Fan, J., Wang, J. (2021). Kinoform Generated Combined with the Error Diffusion Method and the Dynamic Random Phase. In: Guan, M., Na, Z. (eds) Machine Learning and Intelligent Communications. MLICOM 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-030-66785-6_31
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DOI: https://doi.org/10.1007/978-3-030-66785-6_31
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