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Edge-resolved transient imaging (ERTI) is a method for non-line-of-sight imaging that combines the use of direct time of flight for measuring distances with the azimuthal angular resolution afforded by a vertical edge occluder. Recently conceived and demonstrated for the first time, no performance analyses or optimizations of ERTI have appeared in published papers. This paper explains how the difficulty of detection of hidden scene objects with ERTI depends on a variety of parameters, including illumination power, acquisition time, ambient light, visible-side reflectivity, hidden-side reflectivity, target range, and target azimuthal angular position. Based on this analysis, optimization of the acquisition process is introduced whereby the illumination dwell times are varied to counteract decreasing signal-to-noise ratio at deeper angles into the hidden volume. Inaccuracy caused by a coaxial approximation is also analyzed and simulated. 

In time-correlated single-photon counting (TCSPC), photons that arrive during the detector and timing electronics dead times are missed, causing distortion of the detection time distribution. Conventional wisdom holds that TCSPC should be performed with detections in fewer than 5% of illumination cycles to avoid substantial distortion. This requires attenuation and leads to longer acquisition times if the incident flux is too high. Through the example of ranging with a single-photon lidar system, this work demonstrates that accurately modeling the sequence of detection times as a Markov chain allows for measurements at much higher incident flux without attenuation. Our probabilistic model is validated by the close match between the limiting distribution of the Markov chain and both simulated and experimental data, so long as issues of calibration and afterpulsing are minimal. We propose an algorithm that corrects for the distortion in detection histograms caused by dead times without assumptions on the form of the transient light intensity. Our histogram correction yields substantially improved depth imaging performance, and modest additional improvement is achieved with a parametric model assuming a single depth per pixel. We show results for depth and flux estimation with up to 5 photoelectrons per illumination cycle on average, facilitating an increase in time efficiency of more than two orders of magnitude. The use of identical TCSPC equipment in other fields suggests that our modeling and histogram correction could likewise enable high-flux acquisitions in fluorescence lifetime microscopy or quantum optics applications. 

Single-photon lidar (SPL) is a promising technology for depth measurement at long range or from weak reflectors because of the sensitivity to extremely low light levels. However, constraints on the timing resolution of existing arrays of single-photon avalanche diode (SPAD) detectors limit the precision of resulting depth estimates. In this work, we describe an implementation of subtractively-dithered SPL that can recover high-resolution depth estimates despite the coarse resolution of the detector. Subtractively-dithered measurement is achieved by adding programmable delays into the photon timing circuitry that introduce relative time shifts between the illumination and detection that are shorter than the time bin duration. Careful modeling of the temporal instrument response function leads to an estimator that outperforms the sample mean and results in depth estimates with up to 13 times lower root mean-squared error than if dither were not used. The simple implementation and estimation suggest that globally dithered SPAD arrays could be used for high spatial- and temporal-resolution depth sensing. 

Abstract 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 autonomous navigation, reconnaissance, and even medical imaging. The critical challenge of NLOS imaging is that diffuse reflections scatter light in all directions, resulting in weak signals and a loss of directional information. To address this problem, we propose a method for seeing around corners that derives angular resolution from vertical edges and longitudinal resolution from the temporal response to a pulsed light source. We introduce an acquisition strategy, scene response model, and reconstruction algorithm that enable the formation of 2.5-dimensional representations—a plan view plus heights—and a 180^∘field of view for large-scale scenes. Our experiments demonstrate accurate reconstructions of hidden rooms up to 3 meters in each dimension despite a small scan aperture (1.5-centimeter radius) and only 45 measurement locations. 

Liverworts and mosses are a major component of the epiphyte flora of tropical montane forest ecosystems. Canopy access was used to analyse the distribution and vertical stratification of bryophyte epiphytes within tree crowns at nine forest sites across a 3400 m elevational gradient in Peru, from the Amazonian basin to the high Andes. The stable isotope compositions of bryophyte organic material ( 13 C/ 12 C and 18 O/ 16 O) are associated with surface water diffusive limitations and, along with C/N content, provide a generic index for the extent of cloud immersion. From lowland to cloud forest δ 13 C increased from −33‰ to −27‰, while δ 18 O increased from 16.3‰ to 18.0‰. Epiphytic bryophyte and associated canopy soil biomass in the cloud immersion zone was estimated at up to 45 t dry mass ha −1 , and overall water holding capacity was equivalent to a 20 mm precipitation event. The study emphasizes the importance of diverse bryophyte communities in sequestering carbon in threatened habitats, with stable isotope analysis allowing future elevational shifts in the cloud base associated with changes in climate to be tracked.