High-Resolution LiDAR via Upsampling Multiecho Data Obtained From Low-Resolution SPAD Arrays

Spatial resolution is a critical factor in promoting the deployment of Light Detection And Ranging (LiDAR). In our point-scanning single-photon avalanche diode (SPAD) LiDAR at NYCU, the field of view (FOV) of a pixel is designed to be larger than the pixel size to avoid miss-detection of small objects. Therefore, received multiple echoes in a pixel may contain the depth information for immediate neighboring pixels, and this can be exploited to generate higher-resolution depth images. Existing up-sampling/interpolation methods operate on single-echo depth data and may lead to incorrect depth information. In this letter, a SPAD LiDAR with an efficient algorithm is proposed to generate high-resolution (128×256) depth images with a relatively low-resolution (64×128) SPAD array. In the up-sampling operation, the overlapping FOVs in the SPAD LiDAR are exploited to process multi-echo data. In addition, a quantitative metric is developed to evaluate the image quality. Experiment results demonstrate that the proposed approach has better accuracy in depth information and enhances the visual effect of delineating objects in experimental scenes.