Rapid single-photon color imaging of moving objects.

This paper outlines an experimental demonstration of a Bayesian image reconstruction approach to achieve rapid single-photon color imaging of moving objects. The capacity to extract the color of objects is important in a variety of target identification and computer vision applications. Nonetheless, it remains challenging to achieve high-speed color imaging of moving objects in low-photon flux environments. The low-photon regime presents particular challenges for efficient spectral separation and identification, while unsupervised image reconstruction algorithms are often slow and computationally expensive. In this paper, we address both of these difficulties using a combination of hardware and computational solutions. We demonstrate color imaging using a Single-Photon Avalanche Diode (SPAD) detector array for rapid, low-light-level data acquisition, with an integrated color filter array (CFA) for efficient spectral unmixing. High-speed image reconstruction is achieved using a bespoke Bayesian algorithm to produce high-fidelity color videos. The analysis is conducted first on simulated data allowing different pixel formats and photon flux scenarios to be investigated. Experiments are then performed using a plasmonic metasurface-based CFA, integrated with a 64 × 64 pixel format SPAD array. Passive imaging is conducted using white-light illumination of multi-colored, moving targets. Intensity information is recorded in a series of 2D photon-counting SPAD frames, from which accurate color information is extracted using the fast Bayesian method introduced herein. The per-frame reconstruction rate proves to be hundreds of times faster than the previous computational method. Furthermore, this approach yields additional information in the form of uncertainty measures, which can be used to assist with imaging system optimization and decision-making in real-world applications. The techniques demonstrated point the way towards rapid video-rate single-photon color imaging. The developed Bayesian algorithm, along with more advanced SPAD technology and utilization of time-correlated single-photon counting (TCSPC) will permit live 3D, color videography in extremely low-photon flux environments.

High concentration factor diffractive microlenses integrated with CMOS single-photon avalanche diode detector arrays for fill-factor improvement.

Large-format single-photon avalanche diode (SPAD) arrays often suffer from low fill-factors-the ratio of the active area to the overall pixel area. The detection efficiency of these detector arrays can be vastly increased with the integration of microlens arrays designed to concentrate incident light onto the active areas and may be refractive or diffractive in nature. The ability of diffractive optical elements (DOEs) to efficiently cover a square or rectangular pixel, combined with their capability of working as fast lenses (i.e., ∼f/3) makes them versatile and practical lens designs for use in sparse photon applications using microscale, large-format detector arrays. Binary-mask-based photolithography was employed to fabricate fast diffractive microlenses for two designs of 32×32 SPAD detector arrays, each design having a different pixel pitch and fill-factor. A spectral characterization of the lenses is performed, as well as analysis of performance under different illumination conditions from wide- to narrow-angle illumination (i.e., f/2 to f/22 optics). The performance of the microlenses presented exceeds previous designs in terms of both concentration factor (i.e., increase in light collection capability) and lens speed. Concentration factors greater than 33× are achieved for focal lengths in the substrate material as short as 190µm, representing a microlens f-number of 3.8 and providing a focal spot diameter of <4µm. These results were achieved while retaining an extremely high degree of performance uniformity across the 1024 devices in each case, which demonstrates the significant benefits to be gained by the implementation of DOEs as part of an integrated detector system using SPAD arrays with very small active areas.

High-resolution depth profiling using a range-gated CMOS SPAD quanta image sensor.

A CMOS single-photon avalanche diode (SPAD) quanta image sensor is used to reconstruct depth and intensity profiles when operating in a range-gated mode used in conjunction with pulsed laser illumination. By designing the CMOS SPAD array to acquire photons within a pre-determined temporal gate, the need for timing circuitry was avoided and it was therefore possible to have an enhanced fill factor (61% in this case) and a frame rate (100,000 frames per second) that is more difficult to achieve in a SPAD array which uses time-correlated single-photon counting. When coupled with appropriate image reconstruction algorithms, millimeter resolution depth profiles were achieved by iterating through a sequence of temporal delay steps in synchronization with laser illumination pulses. For photon data with high signal-to-noise ratios, depth images with millimeter scale depth uncertainty can be estimated using a standard cross-correlation approach. To enhance the estimation of depth and intensity images in the sparse photon regime, we used a bespoke clustering-based image restoration strategy, taking into account the binomial statistics of the photon data and non-local spatial correlations within the scene. For sparse photon data with total exposure times of 75 ms or less, the bespoke algorithm can reconstruct depth images with millimeter scale depth uncertainty at a stand-off distance of approximately 2 meters. We demonstrate a new approach to single-photon depth and intensity profiling using different target scenes, taking full advantage of the high fill-factor, high frame rate and large array format of this range-gated CMOS SPAD array.

Optical quantum super-resolution imaging and hypothesis testing.

Estimating the angular separation between two incoherent thermal sources is a challenging task for direct imaging, especially at lengths within the diffraction limit. Moreover, detecting the presence of multiple sources of different brightness is an even more severe challenge. We experimentally demonstrate two tasks for super-resolution imaging based on hypothesis testing and quantum metrology techniques. We can significantly reduce the error probability for detecting a weak secondary source, even for small separations. We reduce the experimental complexity to a simple interferometer: we show (1) our set-up is optimal for the state discrimination task, and (2) if the two sources are equally bright, then this measurement can super-resolve their angular separation. Using a collection baseline of 5.3 mm, we resolve the angular separation of two sources placed 15 µm apart at a distance of 1.0 m with a 1.7% accuracy - an almost 3-orders-of-magnitude improvement over shot-noise limited direct imaging.

Simultaneous multi-spectral, single-photon fluorescence imaging using a plasmonic colour filter array.

We present the first realisation of simultaneous multi-spectral fluorescence imaging using a single-photon avalanche diode (SPAD) array, where the spectral unmixing is facilitated by a plasmonic metasurface mosaic colour filter array (CFA). A 64 × 64 pixel format silicon SPAD array is used to record widefield fluorescence and brightfield data from four biological samples. A plasmonic metasurface composed of an arrangement of circular and elliptical nanoholes etched into an aluminium thin film deposited on a glass substrate provides the high transmission efficiency CFA, enabling a bespoke spectral unmixing algorithm to reconstruct high fidelity, full colour images from as few as ∼3 photons per pixel. This approach points the way toward real-time, single-photon sensitive multi-spectral fluorescence imaging. Furthermore, this is possible without additional bulky components such as a filter wheel, prism or diffraction grating, nor the need for multiple sample exposures or multiple detectors.