421 citations · 1.6k across the 35 of their papers we have counts for
14 papers · 1 filter
Bayesian Based Unrolling for Reconstruction and Super-resolution of Single-Photon Lidar Systems
Abderrahim Halimi, Jakeoung Koo, Stephen McLaughlin
Deploying 3D single-photon Lidar imaging in real world applications faces several challenges due to imaging in high noise environments and with sensors having limited resolution. T…
3D Target Detection and Spectral Classification for Single-photon LiDAR Data
Mohamed Amir Alaa Belmekki, Jonathan Leach, Rachael Tobin +3
3D single-photon LiDAR imaging has an important role in many applications. However, full deployment of this modality will require the analysis of low signal to noise ratio target r…
Robust real-time imaging through flexible multimode fibers
Abdullah Abdulaziz, Simon Peter Mekhail, Yoann Altmann +2
Conventional endoscopes comprise a bundle of optical fibers, associating one fiber for each pixel in the image. In principle, this can be reduced to a single multimode optical fibe…
A Bayesian Based Deep Unrolling Algorithm for Single-Photon Lidar Systems
Jakeoung Koo, Abderrahim Halimi, Stephen McLaughlin
Deploying 3D single-photon Lidar imaging in real world applications faces multiple challenges including imaging in high noise environments. Several algorithms have been proposed to…
Fast Task-Based Adaptive Sampling for 3D Single-Photon Multispectral Lidar Data
Mohamed Amir Alaa Belmekki, Rachael Tobin, Gerald S. Buller +2
3D single-photon LiDAR imaging plays an important role in numerous applications. However, long acquisition times and significant data volumes present a challenge to LiDAR imaging.…
Robust and Guided Bayesian Reconstruction of Single-Photon 3D Lidar Data: Application to Multispectral and Underwater Imaging
Abderrahim Halimi, Aurora Maccarone, Robert Lamb +2
3D Lidar imaging can be a challenging modality when using multiple wavelengths, or when imaging in high noise environments (e.g., imaging through obscurants). This paper presents a…
Robust super-resolution depth imaging via a multi-feature fusion deep network
Alice Ruget, Stephen McLaughlin, Robert K. Henderson +3
Three-dimensional imaging plays an important role in imaging applications where it is necessary to record depth. The number of applications that use depth imaging is increasing rap…
Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences
Quentin Legros, Julian Tachella, Rachael Tobin +6
In this paper, we present a new algorithm for fast, online 3D reconstruction of dynamic scenes using times of arrival of photons recorded by single-photon detector arrays. One of t…
Seeing Around Corners with Edge-Resolved Transient Imaging
Joshua Rapp, Charles Saunders, Julián Tachella +7
Non-line-of-sight (NLOS) imaging is a rapidly growing field seeking to form images of objects outside the field of view, with potential applications in search and rescue, reconnais…
EM-based approach to 3D reconstruction from single-waveform multispectral Lidar data
Quentin Legros, Sylvain Meignen, Stephen McLaughlin +1
In this paper, we present a novel Bayesian approach for estimating spectral and range profiles from single-photon Lidar waveforms associated with single surfaces in the photon-limi…
Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events
Yoann Altmann, Stephen McLaughlin, Michael E. Davies
In this paper, we present an algorithm for online 3D reconstruction of dynamic scenes using individual times of arrival (ToA) of photons recorded by single-photon detector arrays.…
Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers
Julián Tachella, Yoann Altmann, Nicolas Mellado +5
Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of…
Long-range depth imaging using a single-photon detector array and non-local data fusion
Susan Chan, Abderrahim Halimi, Feng Zhu +6
The ability to measure and record high-resolution depth images at long stand-off distances is important for a wide range of applications, including connected and automotive vehicle…
Bayesian 3D Reconstruction of Complex Scenes from Single-Photon Lidar Data
Julián Tachella, Yoann Altmann, Ximing Ren +4
Light detection and ranging (Lidar) data can be used to capture the depth and intensity profile of a 3D scene. This modality relies on constructing, for each pixel, a histogram of…