Imaging quality characterization and optimization of segmented planar imaging system based on honeycomb dense azimuth sampling lens array

Segmented planar photoelectric imaging is an advanced computational imaging technology that utilizes photonic integrated circuits (PICs) to achieve the miniaturization of imaging systems. The original radial-spoke lens array has dense radial sampling and coarse azimuthal sampling. The sparsity and inhomogeneity of spatial frequency sampling lead to the loss of spatial frequency information and blurred reconstructed images. In this paper, a honeycomb dense azimuth sampling lens array is proposed, and three baseline pairing methods are designed, which can realize dense azimuth sampling, effectively increase spatial frequency sampling and improve the imaging quality. The signal transmission model of the segmented planar imaging system is established and the imaging process is simulated and analyzed. The simulation results show that the honeycomb lens array improves the azimuth sampling density and spatial frequency coverage, and its imaging quality is significantly improved compared with the hexagonal lens array and the radial-spoke lens array. Furthermore, the optimal choice of the baseline pairing method and the error range of the fill factor and are also given in this paper. The results indicate that the mixed pairing method first ensures low and medium-frequency dense sampling, and then increases high-frequency sampling, which makes the imaging results better than those of the other two baseline pairing methods in terms of image contour, contrast and image detail information. The sampling density of the spatial frequency and the imaging quality can be improved by increasing the fill factor. In the actual manufacturing process, the allowable error range of the fill factor of the lens array is within 5%. The research results will provide theoretical support for the design and development of segmented planar imaging system.