Completely depth-invariant point spread function design via radial lensless imaging

We propose a lensless imaging system based on a full-aperture radial coded mask that produces a depth-invariant point spread function (PSF), enabling all-in-focus image reconstruction from a single PSF calibration. In contrast to conventional lens-based systems—where defocus blur is directly observed—lensless cameras rely on computational reconstruction using a calibrated PSF, making image quality highly sensitive to PSF mismatch. Our radial mask design ensures consistent PSF structure across a wide depth range, mitigating this sensitivity and enabling depth-independent captures. We validate the depth invariance of the proposed mask through experimental PSF analysis, demonstrating high correlation between PSFs captured at depths from 1 cm to 10 cm. We further show, using both simulations and real experiments, that our system enables accurate reconstructions across diverse depth ranges using both optimization-based and data-driven methods. In contrast to restricted-aperture masks, which suffer from depth-dependent degradation and reduced light efficiency, our full-aperture design maintains high signal-to-noise ratio and supports consistent reconstruction even in low-light conditions. Finally, we demonstrate scene reconstruction over a continuous 2–50 cm depth range using a local convolution model and convex optimization, highlighting the practical feasibility of our approach for depth-agnostic lensless imaging.