Non-line-of-sight transparent object detection and reconstruction based on passive single-pixel imaging

Abstract

Abstract Single-pixel imaging (SPI) uses point detectors instead of expensive array sensors to capture images under low light conditions. It therefore provides a solution in detecting objects with weak signals. In this research, we propose a non-line-of-sight (NLOS) 2D transparent object inspection system based on SPI technique. The 2D shape of the transparent object is reconstructed using Total Variation Augmented Lagrangian and Alternating Direction Algorithm (TVAL3) approach by collecting indirect light reflected from the object surface. Theoretical analysis shows that 300 illumination patterns are required to reconstruct a 32 × 32 pixel image, and those patterns are streamed to the digital micromirror device at high speed. Compared to TVAL3 with other methods, better image quality can be obtained with only one-third of illumination patterns. Also, experimental results confirm that this system can obtain transparent object information from reflected light even at a sampling rate of 24%. Furthermore, adjusting the laser wavelength and laser power can improve image quality. The proposed SPI detection system for NLOS transparent objects is an effective method that requires fewer illumination patterns and provides new insights for the detection and reconstruction of NLOS transparent object.