Restoration of Multilayered Single-Photon 3D LiDAR Images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)
60 Downloads (Pure)


This paper presents a new algorithm for the restoration of multilayered three-dimensional laser detection and ranging (3D Lidar) images. For multilayered targets such as semi-transparent surfaces or when the transmitted light of the laser beam is incident on multiple surfaces at different depths, the returned signal may contain multiple peaks. Considering the Poisson statistics of these observations leads to a convex data fidelity term that is regularized using appropriate functions accounting for the spatial correlation between pixels and the sparse depth repartition of targets. More precisely, the spatial correlation is introduced using a convex total variation (TV) regularizer, and a collaborative sparse prior is used to introduce the depth prior knowledge. The resulting minimization problem is solved using the alternating direction method of multipliers (ADMM) that offers good convergence properties. The algorithm was validated using field data representing a man standing 1 meter behind camouflage, at an approximate stand-off distance of $230$m from the system. The results show the benefit of the proposed strategy in that it improves the quality of the imaged objects at different depths and under reduced acquisition times.
Original languageEnglish
Title of host publication2017 25th European Signal Processing Conference (EUSIPCO)
Number of pages5
ISBN (Electronic)9780992862671
Publication statusPublished - 26 Oct 2017
Event25th European Signal Processing Conference 2017 - Greece, Kos, Greece
Duration: 28 Aug 20172 Sept 2017

Publication series

NameEuropean Signal Processing Conference (EUSIPCO)
ISSN (Print)2076-1465


Conference25th European Signal Processing Conference 2017
Abbreviated titleEUSIPCO
Internet address


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