Research on computationally adaptive plenoptic imaging
Lv Yang1, Ning Yu1, Ma Haotong2, Sun Quan1, Zhang Xuanzhe1, Liu Wenguang1, Xu Xiaojun1     
1. College of Interdisciplinary Studies, National University of Defense Technology, Changsha, Hunan 410073, China;
2. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, Sichuan 610209, China

Overview: For the complicated imaging environment with turbulent atmosphere or obstacle interference, the imaging performance of the optics imaging system will seriously decrease. In order to improve the imaging resolution of the complicated imaging system, post image processing and adaptive optics techniques are always utilized. As for post image processing, it has a special condition for image collecting environment, sampling rate and the pre-information of the image, thus it has a large computation load and is difficult to realize real time or near real time processing. Though the traditional adaptive optics technique can detect and compensate for the wavefront distortion information caused by environment, it cannot deal with the problem of anisoplanatic and large field of view applications. The system is complicated, expensive and hard to control, so that it is not available for small equipment. Furthermore, it is a correction system based on the optical field wavefront phase difference, and because of the complicated imaging environment, the obstacles located on the optical propagation pass may modulate the optical field of the target, which results in lacking of target plenoptic information and cannot obtain wavefront distortion of the extended target being partially occluded. It means that the imaging system cannot obtain clear image of the target by adaptive correction and the traditional adaptive optics is not available in the case of complicated occluded imaging environment.

In this article, computational optical imaging technology is introduced to the application of adaptive optics imaging method, based on the advantage of computational optical imaging system. Different from the traditional adaptive optics imaging based on phase conjugation, the computational adaptive plenoptic imaging system is aimed to decrease the amplitude and phase interference caused by the complicated environment based on the computational imaging correlation method. As for computational adaptive plenoptic imaging system, the light-field of the target and obstacle are measured together, and then according to distribution characteristics of the four-dimensional optical field information between the target and the obstacle, target and obstacle can be effectively separated. On one hand, this technique can be used to detect and recover the wavefront distortion caused by interference in the large field of view, and adaptively compensate for complicated wavefront aberration by means of computation. On the other hand, it can delete the certain effect caused by the obstacle performing to the target optical field in the complicated environment. Compared with the traditional adaptive optics imaging method, the proposed method has a larger detecting field of view, and can directly analyze and compute wavefront information based on the extended target. The computational plenoptic imaging system has no active optical equipment or dynamic equipment. It utilizes the computational method instead of mechanical deformable mirror to realize phase compensation, and can adaptively compensate for the complicated wavefront phase perturbation in the imaging space. It has the advantages of compact structure and low cost. Furthermore, it can delete the interferential imaging effect from the obstacle located in the optical pass of higher dimensional optical field to obtain clear images.