Plug-and-play algorithm for 3D guided video super-resolution of single-photon LiDAR data.

Single-photon avalanche diodes (SPADs) are advanced sensors capable of detecting individual photons and recording their arrival times with picosecond resolution using time-correlated single-photon counting (TCSPC) detection techniques. They are used in various applications, such as LiDAR and low-light imaging. These single-photon cameras can capture high-speed sequences of binary single-photon images, offering great potential for reconstructing 3D environments with high motion dynamics.

Super-resolution depth imaging via processing of compact single-photon histogram parameters.

Time-of-flight (ToF) imaging is widely used in consumer electronics for depth perception, with compact ToF sensors often representing their data as histograms of photon arrival times for each pixel. These histograms capture detailed temporal information that enables advanced computational techniques, such as super-resolution, to reconstruct high-resolution depth images even from low-resolution sensors by leveraging the full temporal structure of the data. However, transferring full histogram data is impractical for compact systems due to the large amount of data.

Translated object identification for efficient ghost imaging.

Alignment of a single-pixel quantum ghost imaging setup is complex and requires extreme precision. Due to misalignment, easily created by human error in the alignment process, reconstructed images are often translated off the central imaging axis. This becomes problematic for intelligent object detection and identification in fast imaging cases, as these algorithms are unable to achieve early image identification.

The importance of molecular axis alignment and symmetry-breaking in photoelectron elliptical dichroism.

Photoelectron angular distributions (PADs) produced from the photoionization of chiral molecules using elliptically polarized light exhibit a forward/backward asymmetry with respect to the optical propagation direction. By recording these distributions using the velocity-map imaging (VMI) technique, the resulting photoelectron elliptical dichroism (PEELD) has previously been demonstrated as a promising spectroscopic tool for studying chiral molecules in the gas phase. The use of elliptically polarized laser pulses, however, produces PADs (and consequently, PEELD distributions) that do not exhibit cylindrical symmetry about the propagation axis.

Video super-resolution for single-photon LIDAR.

3D time-of-flight (ToF) image sensors are used widely in applications such as self-driving cars, augmented reality (AR), and robotics. When implemented with single-photon avalanche diodes (SPADs), compact, array format sensors can be made that offer accurate depth maps over long distances, without the need for mechanical scanning. However, array sizes tend to be small, leading to low lateral resolution, which combined with low signal-to-background ratio (SBR) levels under high ambient illumination, may lead to difficulties in scene interpretation.

Pixels2Pose: Super-resolution time-of-flight imaging for 3D pose estimation.

Single-photon-sensitive depth sensors are being increasingly used in next-generation electronics for human pose and gesture recognition. However, cost-effective sensors typically have a low spatial resolution, restricting their use to basic motion identification and simple object detection. Here, we perform a temporal to spatial mapping that drastically increases the resolution of a simple time-of-flight sensor, i.

Arbitrary image reinflation: A deep learning technique for recovering 3D photoproduct distributions from a single 2D projection.

Many charged particle imaging measurements rely on the inverse Abel transform (or related methods) to reconstruct three-dimensional (3D) photoproduct distributions from a single two-dimensional (2D) projection image. This technique allows for both energy- and angle-resolved information to be recorded in a relatively inexpensive experimental setup, and its use is now widespread within the field of photochemical dynamics. There are restrictions, however, as cylindrical symmetry constraints on the overall form of the distribution mean that it can only be used with a limited range of laser polarization geometries.

High-speed object detection with a single-photon time-of-flight image sensor.

3D time-of-flight (ToF) imaging is used in a variety of applications such as augmented reality (AR), computer interfaces, robotics and autonomous systems. Single-photon avalanche diodes (SPADs) are one of the enabling technologies providing accurate depth data even over long ranges. By developing SPADs in array format with integrated processing combined with pulsed, flood-type illumination, high-speed 3D capture is possible.

Robust super-resolution depth imaging via a multi-feature fusion deep network.

The number of applications that use depth imaging is increasing rapidly, e.g. self-driving autonomous vehicles and auto-focus assist on smartphone cameras.

Artificial Neural Networks for Noise Removal in Data-Sparse Charged Particle Imaging Experiments.

We present the first demonstration of artificial neural networks (ANNs) for the removal of Poissonian noise in charged particle imaging measurements with very low overall counts. The approach is successfully applied to both simulated and real experimental image data relating to the detection of photoions/photoelectrons in unimolecular photochemical dynamics studies. Specific examples consider the multiphoton ionization of pyrrole and (S)-camphor.