High-Resolution and Large Field-of-View Computational Imaging Method

High-resolution and large field-of-view imaging allows aerospace remote sensing to perform finer perception over a wider range. Based on the computational imaging basic principle, this paper proposes a suboptimal computational imaging design method with a large field-of-view. The imaging process, is divided into two components: hardware imaging and software restoration. The design method that combines software and hardware can fully incorporate the advantages of the two, reducing the difficulty of hardware design and improving the overall performance of system imaging. In terms of hardware design, a suboptimal optical design method is proposed, which seeks a consistent suboptimal point expansion function in a larger field-of-view rather than using the design degree of freedom resources in a small field-of-view. The imaging field-of-view under the state of limited design degree of freedom is enlarged when combined with the image restoration method. The off-axis three-mirror optical system is designed using the suboptimal method, which increases the design field-of-view to 5 degrees, which is more than twice the field-of-view of conventional design method. When combined with the nonlinear image restoration method based on deep learning, the structural similarity of similar targets is more than 85%, and that of different types of targets is more than 80%, which effectively realizes the design of high-resolution and large field-of-view imaging system, and provides a new method for aerospace remote sensing wide-area fine observation.