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.