Pseudo-Random Spread Spectrum Technique Based Single-Pixel Imaging Method

With the increasing interest in autonomous transport, machine vision and remote sensing, several three-dimensional time-of-flight (ToF) imaging technologies that can recover object's fine details have been presented. Single-pixel imaging provides an alternative to ToF photon-counting imaging with a scanned laser spot. In this work, we present a pseudo-random spread spectrum technique based single-pixel ToF imaging method, which can avoid the range ambiguity, broaden the range of signal frequencies. In addition, the Quadratic Correlation Reconstruction algorithm is applied to further increase the accuracy. With environmental light and system noise, compared to the conventional ToF single-pixel lidar we demonstrate that this approach enhances scene reconstruction quality with depth accuracy improvements of 10.5. This method may open a new gate for improved non-scanning lidar systems.