Ultrafast and hypersensitive phase imaging of propagating internodal current flows in myelinated axons and electromagnetic pulses in dielectrics

Single-Shot Intensity- and Phase-Sensitive Compressive Sensing-Based Coherent Modulation Ultrafast Imaging

Ultrafast imaging can capture the dynamic scenes with a nanosecond and even femtosecond temporal resolution. Complementarily, phase imaging can provide the morphology, refractive index, or thickness information that intensity imaging cannot represent. Therefore, it is important to realize the simultaneous ultrafast intensity and phase imaging for achieving as much information as possible in the detection of ultrafast dynamic scenes. Here, we report a single-shot intensity- and phase-sensitive compressive sensing-based coherent modulation ultrafast imaging technique, shortened as CS-CMUI, which integrates coherent modulation imaging, compressive imaging, and streak imaging. We theoretically demonstrate through numerical simulations that CS-CMUI can obtain both the intensity and phase information of the dynamic scenes with ultrahigh fidelity. Furthermore, we experimentally build a CS-CMUI system and successfully measure the intensity and phase evolution of a multimode Q-switched laser pulse and the dynamical behavior of laser ablation on an indium tin oxide thin film. It is anticipated that CS-CMUI enables a profound comprehension of ultrafast phenomena and promotes the advancement of various practical applications, which will have substantial impact on fundamental and applied sciences.

Tutorial on compressed ultrafast photography

Significance

Compressed ultrafast photography (CUP) is currently the world's fastest single-shot imaging technique. Through the integration of compressed sensing and streak imaging, CUP can capture a transient event in a single camera exposure with imaging speeds from thousands to trillions of frames per second, at micrometer-level spatial resolutions, and in broad sensing spectral ranges.

Aim

This tutorial aims to provide a comprehensive review of CUP in its fundamental methods, system implementations, biomedical applications, and prospect.

Approach

A step-by-step guideline to CUP's forward model and representative image reconstruction algorithms is presented with sample codes and illustrations in Matlab and Python. Then, CUP's hardware implementation is described with a focus on the representative techniques, advantages, and limitations of the three key components-the spatial encoder, the temporal shearing unit, and the two-dimensional sensor. Furthermore, four representative biomedical applications enabled by CUP are discussed, followed by the prospect of CUP's technical advancement.

Conclusions

CUP has emerged as a state-of-the-art ultrafast imaging technology. Its advanced imaging ability and versatility contribute to unprecedented observations and new applications in biomedicine. CUP holds great promise in improving technical specifications and facilitating the investigation of biomedical processes.

Flexible and accurate total variation and cascaded denoisers-based image reconstruction algorithm for hyperspectrally compressed ultrafast photography

Hyperspectrally compressed ultrafast photography (HCUP) based on compressed sensing and time- and spectrum-to-space mappings can simultaneously realize the temporal and spectral imaging of non-repeatable or difficult-to-repeat transient events with a passive manner in single exposure. HCUP possesses an incredibly high frame rate of tens of trillions of frames per second and a sequence depth of several hundred, and therefore plays a revolutionary role in single-shot ultrafast optical imaging. However, due to ultra-high data compression ratios induced by the extremely large sequence depth, as well as limited fidelities of traditional algorithms over the image reconstruction process, HCUP suffers from a poor image reconstruction quality and fails to capture fine structures in complex transient scenes. To overcome these restrictions, we report a flexible image reconstruction algorithm based on a total variation (TV) and cascaded denoisers (CD) for HCUP, named the TV-CD algorithm. The TV-CD algorithm applies the TV denoising model cascaded with several advanced deep learning-based denoising models in the iterative plug-and-play alternating direction method of multipliers framework, which not only preserves the image smoothness with TV, but also obtains more priori with CD. Therefore, it solves the common sparsity representation problem in local similarity and motion compensation. Both the simulation and experimental results show that the proposed TV-CD algorithm can effectively improve the image reconstruction accuracy and quality of HCUP, and may further promote the practical applications of HCUP in capturing high-dimensional complex physical, chemical and biological ultrafast dynamic scenes.

Single-pulse real-time billion-frames-per-second planar imaging of ultrafast nanoparticle-laser dynamics and temperature in flames

Unburnt hydrocarbon flames produce soot, which is the second biggest contributor to global warming and harmful to human health. The state-of-the-art high-speed imaging techniques, developed to study non-repeatable turbulent flames, are limited to million-frames-per-second imaging rates, falling short in capturing the dynamics of critical species. Unfortunately, these techniques do not provide a complete picture of flame-laser interactions, important for understanding soot formation. Furthermore, thermal effects induced by multiple consecutive pulses modify the optical properties of soot nanoparticles, thus making single-pulse imaging essential. Here, we report single-shot laser-sheet compressed ultrafast photography (LS-CUP) for billion-frames-per-second planar imaging of flame-laser dynamics. We observed laser-induced incandescence, elastic light scattering, and fluorescence of soot precursors - polycyclic aromatic hydrocarbons (PAHs) in real-time using a single nanosecond laser pulse. The spatiotemporal maps of the PAHs emission, soot temperature, primary nanoparticle size, soot aggregate size, and the number of monomers, present strong experimental evidence in support of the theory and modeling of soot inception and growth mechanism in flames. LS-CUP represents a generic and indispensable tool that combines a portfolio of ultrafast combustion diagnostic techniques, covering the entire lifecycle of soot nanoparticles, for probing extremely short-lived (picoseconds to nanoseconds) species in the spatiotemporal domain in non-repeatable turbulent environments. Finally, LS-CUP's unparalleled capability of ultrafast wide-field temperature imaging in real-time is envisioned to unravel mysteries in modern physics such as hot plasma, sonoluminescence, and nuclear fusion.

Compressed ultrahigh-speed single-pixel imaging by swept aggregate patterns

Single-pixel imaging (SPI) has emerged as a powerful technique that uses coded wide-field illumination with sampling by a single-point detector. Most SPI systems are limited by the refresh rates of digital micromirror devices (DMDs) and time-consuming iterations in compressed-sensing (CS)-based reconstruction. Recent efforts in overcoming the speed limit in SPI, such as the use of fast-moving mechanical masks, suffer from low reconfigurability and/or reduced accuracy. To address these challenges, we develop SPI accelerated via swept aggregate patterns (SPI-ASAP) that combines a DMD with laser scanning hardware to achieve pattern projection rates of up to 14.1 MHz and tunable frame sizes of up to 101×103 pixels. Meanwhile, leveraging the structural properties of S-cyclic matrices, a lightweight CS reconstruction algorithm, fully compatible with parallel computing, is developed for real-time video streaming at 100 frames per second (fps). SPI-ASAP allows reconfigurable imaging in both transmission and reflection modes, dynamic imaging under strong ambient light, and offline ultrahigh-speed imaging at speeds of up to 12,000 fps.