Fast-zoom and high-resolution sparse compound-eye camera based on dual-end collaborative optimization
Yi Zheng, Haoran Zhang, Xiaowei Li, You‐Ran Zhao, Zhaosong Li, Ye-Hao Hou, Chao Liu, Qiong‐Hua Wang
Abstract
Due to the limitations of spatial bandwidth product and data transmission bandwidth, the field of view, resolution, and imaging speed constrain each other in an optical imaging system. Here, a fast-zoom and high-resolution sparse compound-eye camera (CEC) based on dual-end collaborative optimization is proposed, which provides a cost-effective way to break through the trade-off among the field of view, resolution, and imaging speed. In the optical end, a sparse CEC based on liquid lenses is designed, which can realize large-field-of-view imaging in real time, and fast zooming within 5 ms. In the computational end, a disturbed degradation model driven super-resolution network (DDMDSR-Net) is proposed to deal with complex image degradation issues in actual imaging situations, achieving high-robustness and high-fidelity resolution enhancement. Based on the proposed dual-end collaborative optimization framework, the angular resolution of the CEC can be enhanced from 71.6" to 26.0", which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth. Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images, kilometer-level long-distance detection, and dynamic imaging and precise recognition of targets of interest.