An improved single-photon lidar imaging algorithm based on Unmixing

In order to meet the needs of single-photon lidar imaging fields such as unmanned driving and remote sensing mapping, imaging algorithms usually need to deal with extreme situations such as weak echo and high noise.How to extract effective information and construct target object depth and reflectivity information has become a research hotspot in the field of imaging. At present, the denoising of single-photon lidar imaging algorithms requires knowing the depth range of the target object in advance, which cannot be applied to the case where the depth range is unknown.Therefore, based on the demixing algorithm, an adaptive depth estimation and improved windowed review denoising processing algorithm are proposed. The simulation results verify the effectiveness of the algorithm. The results show that the MSE of the reflectivity of the proposed algorithm is not more than 1dB compared with the unmixing algorithm when the distance is unknown, and the difference between the distance estimation and the result of the unmixing algorithm is not more than 0.05m.