Intensity-guided depth image estimation in long-range lidar

• Published in: Optics and lasers in engineering 2022-08, Vol.155, p.107054, Article 107054
• Main Authors: Wu, Miao, Lu, Yu, Li, Haochen, Mao, Tianyi, Guan, Yanqiu, Zhang, Labao, He, Weiji, Wu, Peiheng, Chen, Qian
• Format: Article
• Language: English
• Subjects: ADMM; Depth image estimation; Intensity guidance; Multi-scale superpixels; Single-photon counting lidar; Temporal correlation
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2022.107054

•Guidance of intensity on depth estimation is emphasized for its sharp edge•Multi-scale superpixels and fast windows are used to solve large but sparse noisy data•Cost function is modified to balance between smoothness and preserving details•Results show accurate depth estimation of long-rang targets in photon-starved regime Long-range lidar systems usually record large but extremely sparse data cubes. It is a great challenge to estimate accurate depth images of the photon-starved regime with fewer memory requirements and lower computational complexity. An intensity-guided method is introduced to estimate the depth image by using temporal-spatial correlation of the reflected signals. Multi-scale superpixels and fast time-domain windows are established in the preprocessing step, leading to smaller data cubes with reduced empty and noisy pixels. To strike a balance between smoothness and preserving sharp edges, the fast-converging alternating direction method of multipliers (ADMM) is used in the modified cost function to estimate depth images. Experimental results show that the proposed method yields better depth estimates than other state-of-the-art methods, especially for long-rang targets of field experiments with a low signal return level of ∼1 photon per pixel.