Single-Pixel Three-Dimensional Compressive Imaging System Using Volume Structured Illumination

Single-pixel imaging enables two-dimensional image capture through a single-pixel detector, yet extending this to three-dimensional or higher-dimensional information capture in single-pixel optical imaging systems has remained a challenging problem. In this study, we present a single-pixel camera system for three-dimensional (3D) imaging based on compressed sensing (CS) with continuous wave (CW) pseudo-random volume structured illumination. An estimated image, which incorporates both spatial and depth information of a 3D scene, is reconstructed using an L1-norm minimization reconstruction algorithm. This algorithm employs prior knowledge of non-overlapping objects as a constraint in the target space, resulting in improved noise performance in both numerical simulations and physical experiments. Our simulations and experiments demonstrate the feasibility of the proposed 3D CS framework. This approach achieves compressive sensing in a 3D information capture system with a measurement ratio of 19.53%. Additionally, we show that our CS 3D capturing system can accurately reconstruct the color of a target using color filter modulation.