• Laser & Optoelectronics Progress
  • Vol. 57, Issue 2, 20001 (2020)
Shao Xiaopeng*, Liu Fei, Li Wei, Yang Liming, Yang Siyuan, and Liu Jiawei
Author Affiliations
  • School of Physics and Optoelectronic Engineering, Xidian University, Xi''an, Shaanxi 710071, China
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    DOI: 10.3788/LOP57.020001 Cite this Article Set citation alerts
    Shao Xiaopeng, Liu Fei, Li Wei, Yang Liming, Yang Siyuan, Liu Jiawei. Latest Progress in Computational Imaging Technology and Application[J]. Laser & Optoelectronics Progress, 2020, 57(2): 20001 Copy Citation Text show less

    Abstract

    Computational imaging technology (CIT) refers to a novel imaging method that is different from the “what you see is what you get” information acquisition and processing methods of traditional optical imaging. With the development of new optoelectronic devices and the improvement of hardware computing capabilities, it has shown a booming trend in the field of optoelectronic imaging. By using CIT to obtain and calculate the information of light field, the information utilization and interpretation capability can be superior to traditional imaging, which can realize the requirements of “higher (resolution), farther (detection range), and larger (optical field of view)” of photoelectric imaging. We start from the description of information acquisition and loss process of the imaging chain, and further analyze the acquisition and interpretation of multi-physical information of light field through several typical computational imaging methods, such as scattering imaging, polarization imaging, and bionic imaging, and the principles of them are discussed in detail. According to the trend of imaging technology, we put forward prospectively the design idea of computational optical system based super large-aperture telescopes. Since CIT has significant advantages in improving imaging resolution, increasing detection distance, expanding imaging field of view, and reducing the size and power consumption of optical systems, it is expected to realize the imaging through the fog with longer distance and through biological tissues at a larger depth.
    Shao Xiaopeng, Liu Fei, Li Wei, Yang Liming, Yang Siyuan, Liu Jiawei. Latest Progress in Computational Imaging Technology and Application[J]. Laser & Optoelectronics Progress, 2020, 57(2): 20001
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