@inproceedings{4d4f276d92824d54a407f7f093668cf4,
title = "3D computational imaging for photonic LiDAR with high noise resilience and photon efficiency",
abstract = "In this work, we introduce a new computational imaging pipeline for a single photon sensitive LiDAR system, which incorporates an image reconstruction module with a point cloud processing module to improve noise resilience and photon efficiency. The image reconstruction module is based on a 3D extension of an iterative image restoration algorithm in a constrained maximum likelihood framework. The point cloud processing module consists of a hierarchical point cloud denoising and segmentation scheme, which produces a refined point cloud data for 3D image reconstruction. Experimental results demonstrate the effectiveness of the proposed computational imaging method under robust operating conditions.",
keywords = "computational imaging, photon efficiency, point cloud processing, single photon LiDAR",
author = "Yunping Fang and Hongtao Xia and Hong Man",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Photonics for Quantum 2025 ; Conference date: 16-06-2025 Through 20-06-2025",
year = "2025",
doi = "10.1117/12.3063174",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
editor = "Michael Reimer and Nir Rotenberg",
booktitle = "Photonics for Quantum 2025",
}