计算成像是一种不仅依赖于光学物理器件,还依赖于光学调制和重构算法的成像技术,为突破传统成像系统在时空分辨率和探测灵敏度方面的限制提供了新的思路。计算鬼成像(CGI)作为计算成像领域发展最迅速的分支之一,近些年被广泛应用于单像素成像、超分辨率成像、生物医学、信息加密、激光雷达以及湍流环境下的信息传输等领域。本文综述了影响CGI质量的两大关键技术——照明图案构造方法与图像重构算法的研究进展,主要介绍了随机矩阵、有序Hadamard矩阵、正交变换类矩阵的构造方法,并且讨论了在传统关联重构算法和新型深度学习重构算法下,各种照明图案的成像性能。最后,对照明图案构造方法及重构算法进行了总结,并对CGI技术发展前景进行了展望。

Computational imaging is an imaging technology that not only relies on optical physical devices, but also relies on optical modulation and reconstruction algorithm. It provides new ideas for breaking through the limitations of traditional imaging systems in terms of temporal and spatial resolution and detection sensitivity. Computational ghost imaging (CGI) is one of the fastest-growing branches in the field of computational imaging, it has been widely used in single-pixel imaging, super-resolution imaging, biomedicine, information encryption, lidar, and information transmission under turbulence in recent years. In this paper, we summarize the progress of construction methods of illumination patterns and image reconstruction algorithms, which are two key technologies that affect quality of CGI. We mainly introduce the construction methods of random matrix, the orderly Hadamard matrix, orthogonal transformation matrix, and discuss the imaging performance of various illumination patterns under traditional correlation reconstruction algorithms and novel deep learning reconstruction algorithms. Finally, the construction methods of illumination patterns and reconstruction algorithms are summarized, and the development prospect of CGI technology is also discussed.