Ghost identification based on single-pixel imaging in big data environment.
Ghost identification based on single-pixel imaging in big data environment.
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DOI：
10.1364/oe.25.016509
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发表时间：
2017-07
期刊：
影响因子：
3.8
通讯作者：
Wen Chen
中科院分区：
文献类型：
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作者：
Wen Chen
近年来，单像素成像已经成为最有趣和最有前途的成像技术之一，用于各种应用。在本文中，一个大数据环境，第一次我的知识是设计和引入到单像素鬼成像信息安全。通过单像素桶检测器记录许多系列的一维密文，形成大数据环境。通过使用分层结构，基于鬼成像对多个隐藏输入进行进一步编码，并将其对应的密文合成到大数据环境中，用于验证隐藏鬼和识别目标鬼。这一新发现可以为探索基于单像素成像的更多应用开辟不同的研究视角。
In recent years, single-pixel imaging has become one of the most interesting and promising imaging technologies for various applications. In this paper, a big data environment for the first time to my knowledge is designed and introduced into single-pixel ghost imaging for securing information. Many series of one-dimensional ciphertexts are recorded by a single-pixel bucket detector to form a big data environment. Several hidden inputs are further encoded based on ghost imaging by using hierarchical structure, and their corresponding ciphertexts are synthesized into the big data environment for verifying the hidden ghosts and identifying the targeted ghosts. This new finding could open up a different research perspective for exploring more applications based on single-pixel imaging.