All-optical object identification and three-dimensional reconstruction based on optical computing metasurface
Dingyu Xu, Wenhao Xu, Qiang Yang, Wenshuai Zhang, Shuangchun Wen, Hailu Luo
Abstract
Object identification and three-dimensional reconstruction techniques are always attractive research interests in machine vision, virtual reality, augmented reality, and biomedical engineering. Optical computing metasurface, as a two-dimensional artificial design component, has displayed the supernormal character of controlling phase, amplitude, polarization, and frequency distributions of the light beam, capable of performing mathematical operations on the input light field. Here, we propose and demonstrate an all-optical object identification technique based on optical computing metasurface, and apply it to 3D reconstruction. Unlike traditional mechanisms, this scheme reduces memory consumption in the processing of the contour surface extraction. The identification and reconstruction of experimental results from high-contrast and low-contrast objects agree well with the real objects. The exploration of the all-optical object identification and 3D reconstruction techniques provides potential applications of high efficiencies, low consumption, and compact systems.