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ISSN: 1023-5086

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ISSN: 1023-5086

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Opticheskii Zhurnal

A full-text English translation of the journal is published by Optica Publishing Group under the title “Journal of Optical Technology”

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Study on the key technology of optical encryption based on adaptive compressive ghost imaging for large-sized object

For Russian citation (Opticheskii Zhurnal):

Leihong Zhang, Zilan Pan, Guoliang Zhou Study on the key technology of optical encryption based on adaptive compressive ghost imaging for large-sized object (Исследование ключевых технологий оптического кодирования на основе адаптивной компрессивной призрачной съемки крупноразмерных объектов) [на англ. яз.] // Оптический журнал. 2017. Т. 84. № 7. С. 52–58.

 

Leihong Zhang, Zilan Pan, Guoliang Zhou Study on the key technology of optical encryption based on adaptive compressive ghost imaging for large-sized object (Исследование ключевых технологий оптического кодирования на основе адаптивной компрессивной призрачной съемки крупноразмерных объектов) [in English] // Opticheskii Zhurnal. 2017. V. 84. № 7. P. 52–58.

For citation (Journal of Optical Technology):

Leihong Zhang, Zilan Pan, and Guoliang Zhou, "Study on the key technology of optical encryption based on adaptive compressive ghost imaging for a large-sized object," Journal of Optical Technology. 84(7), 471-476 (2017). https://doi.org/10.1364/JOT.84.000471

Abstract:

Computational ghost imaging is a good optical encryption method, but it can hardly imaging for large-sized object or the time is long. To solve the problem, we propose a novel optical encryption method based on block adaptive compressive sensing with computational ghost imaging. In this model, we divide the large-sized image into several blocks, then every block is considered as a single image to finish ghost imaging, every block has its own sampling ratio according to human visual system. In the recovery process, we use compressive sensing algorithm to reconstruct the image. Compared with computational ghost imaging, the quality of recovery image is better, so large-sized image can also be recovered with high quality with this method, and the number of transmitted information is reduced in contrast with block computational ghost imaging so that it can use fewer spaces, highefficiency data storage or transmission. This technique can be immediately applied to imaging applications and data storage with the advantages of high quality of reconstructed information and high security, fast transmission.

Keywords:

computational ghost imaging, block computational ghost imaging, compressive sensing algorithm

Acknowledgements:

This study is supported by the National Natural Science Foundation of China (Grant No. 61405115), the Natural Science Foundation of Shanghai (Grant No. 14ZR1428400), Innovation Project of Shanghai Municipal Education Commission (Grant No. 14YZ099).

OCIS codes: 110.1085, 110.1758, 110.3010, 060.4785

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