
 Spatiotemporal sculpturing of light pulse with ultimately sophisticated structures represents the holy grail of the human everlasting pursue of ultra-fast information transmission and processing as well as ultra-intense energy concentration and extraction. It also holds the key to unlock new extraordinary fundamental physical effects. Traditionally, spatiotemporal light pulses are always treated as spatiotemporally separable wave packet as solution of the Maxwell’s equations. In the past decade, however, more generalized forms of spatiotemporally nonseparable solution started to emerge with growing importance for their striking physical effects. This roadmap intends to highlight the recent advances in the creation and control of increasingly complex spatiotemporally sculptured pulses, from spatiotemporally separable to complex nonseparable states, with diverse geometric and topological structures, presenting a bird’s eye viewpoint on the zoology of spatiotemporal light fields and the outlook of future trends and open challenges.

https://iopscience.iop.org/article/10.1088/2040-8986/ace4dc/pdf

Roadmap on spatiotemporal light fields

Many studies have recently used several deep learning methods for detecting skin cancer. However, hyperspectral imaging (HSI) is a noninvasive optics system that can obtain wavelength information on the location of skin cancer lesions and requires further investigation. Hyperspectral technology can capture hundreds of narrow bands of the electromagnetic spectrum both within and outside the visible wavelength range as well as bands that enhance the distinction of image features. The dataset from the ISIC library was used in this study to detect and classify skin cancer on the basis of basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and seborrheic keratosis (SK). The dataset was divided into training and test sets, and you only look once (YOLO) version 5 was applied to train the model. The model performance was judged according to the generated confusion matrix and five indicating parameters, including precision, recall, specificity, accuracy, and the F1-score of the trained model. Two models, namely, hyperspectral narrowband image (HSI-NBI) and RGB classification, were built and then compared in this study to understand the performance of HSI with the RGB model. Experimental results showed that the HSI model can learn the SCC feature better than the original RGB image because the feature is more prominent or the model is not captured in other categories. The recall rate of the RGB and HSI models were 0.722 to 0.794, respectively, thereby indicating an overall increase of 7.5% when using the HSI model.

/pdf/classification-of-skin-cancer-using-novel-hyperspectral-1heuyzm4.pdf

Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5

Forgery and tampering continue to provide unnecessary economic burdens. Although new anti-forgery and counterfeiting technologies arise, they inadvertently lead to the sophistication of forgery techniques over time, to a point where detection is no longer viable without technological aid. Among the various optical techniques, one of the recently used techniques to detect counterfeit products is HSI, which captures a range of electromagnetic data. To aid in the further exploration and eventual application of the technique, this study categorizes and summarizes existing related studies on hyperspectral imaging and creates a mini meta-analysis of this stream of literature. The literature review has been classified based on the product HSI has used in counterfeit documents, photos, holograms, artwork, and currency detection.

/pdf/recent-advances-in-counterfeit-art-document-photo-hologram-1spieyy3.pdf

Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging

Unmanned Aerial Vehicles (UAVs) equipped with air quality sensors offer a powerful solution for increasing the spatial and temporal resolution of air quality data, searching and detecting emission sources, and monitoring emissions from fixed and mobile sources. Despite the numerous advantages of using UAVs, their use, however, presents several challenges that limit their broader adoption. For example, UAVs require efficient algorithms and components to minimize power consumption, the overall payload used on UAVs needs to be small to ensure optimal portability which poses limitations on the sensors that can be integrated with UAVs, and there is a need for specialized algorithms, e.g., for identifying and locating air pollution sources. Currently, most solutions for UAV-based air quality monitoring focus on specific challenges or demonstrating the potential of using UAVs, and there is a lack of comprehensive overview of the research field and its open challenges. In this paper, we contribute a systematic review of UAV-based air quality monitoring, highlighting and analyzing technical solutions and challenges, and identifying open challenges with the aim of providing a research roadmap for the path forward. 

/pdf/unmanned-aerial-vehicles-for-air-pollution-monitoring-a-1cftk98q.pdf

Unmanned Aerial Vehicles for Air Pollution Monitoring: A survey

A rapid and nondestructive method for identification of soybean protein in minced chicken meat based on visible-near infrared hyperspectral imaging (HSI) technology and VGG16-SVM model was proposed in this study. The hyperspectral data from 400.89 nm to 1000.19 nm of samples with different soybean protein contents were collected. Spectral data was transformed into spectrograms through Continuous wavelet transform (CWT). Comparing with other methods, the optimum data preprocessing results were obtained for the subsequent research. Then, VGG16-SVM model based on VGG16 network in which fully connected layer was replaced by support vector machine (SVM) was established to identify soybean protein in minced chicken meat. The results showed that VGG16-SVM model with radial basis function (RBF) as kernel function performed best and the classification accuracy reached 98.1%. Meanwhile, the proposed model was superior to the SVM, convolution neural network (CNN) and VGG16 model. It is feasible and effective for combining HSI technology and VGG16-SVM to realize nondestructive identification of soybean protein in minced chicken meat. 

Nondestructive identification of soybean protein in minced chicken meat based on hyperspectral imaging and VGG16-SVM

Air pollution has emerged as a global problem in recent years. Particularly, particulate matter (PM2.5) with a diameter of less than 2.5 μm can move through the air and transfer dangerous compounds to the lungs through human breathing, thereby creating major health issues. This research proposes a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques. By modeling the visible-light HSI technology of the aerial camera, the image acquired by the drone camera is endowed with hyperspectral information. Two methods are used for the classification of the images. That is, 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) are paired with VGG-16 (Visual Geometry Group) to find the optical properties of air pollution. The images are classified into good, moderate, and severe based on the concentration of PM2.5 particles in the images. The results suggest that the PCA + VGG-16 has the highest average classification accuracy of 85.93%.

/pdf/air-pollution-detection-using-a-novel-snap-shot-1pg0iwge.pdf

Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique

Abstract Femtosecond lasers are powerful in studying matter’s ultrafast dynamics within femtosecond to attosecond time scales. Drawing a three-dimensional (3D) topological map of the optical field of a femtosecond laser pulse including its spatiotemporal amplitude and phase distributions, allows one to predict and understand the underlying physics of light interaction with matter, whose spatially resolved transient dielectric function experiences ultrafast evolution. However, such a task is technically challenging for two reasons: first, one has to capture in single-shot and squeeze the 3D information of an optical field profile into a two-dimensional (2D) detector; second, typical detectors are only sensitive to intensity or amplitude information rather than phase. Here we have demonstrated compressed optical field topography (COFT) drawing a 3D map for an ultrafast optical field in single-shot, by combining the coded aperture snapshot spectral imaging (CASSI) technique with a global 3D phase retrieval procedure. COFT can, in single-shot, fully characterize the spatiotemporal coupling of a femtosecond laser pulse, and live stream the light-speed propagation of an air plasma ionization front, unveiling its potential applications in ultrafast sciences. 

/pdf/single-shot-compressed-optical-field-topography-2d84s8i5.pdf

Single-shot compressed optical field topography

Fourier-transform spectral imaging captures frequency-resolved images with high spectral resolution, broad spectral range, high photon flux, and low stray light. In this technique, spectral information is resolved by taking Fourier transformation of the interference signals of two copies of the incident light at different time delays. The time delay should be scanned at a high sampling rate beyond the Nyquist limit to avoid aliasing, at the price of low measurement efficiency and stringent requirements on motion control for time delay scan. Here we propose, what we believe to be, a new perspective on Fourier-transform spectral imaging based on a generalized central slice theorem analogous to computerized tomography, using an angularly dispersive optics decouples measurements of the spectral envelope and the central frequency. Thus, as the central frequency is directly determined by the angular dispersion, the smooth spectral-spatial intensity envelope is reconstructed from interferograms measured at a sub-Nyquist time delay sampling rate. This perspective enables high-efficiency hyperspectral imaging and even spatiotemporal optical field characterization of femtosecond laser pulses without a loss of spectral and spatial resolutions.

Generalized central slice theorem perspective on Fourier-transform spectral imaging at a sub-Nyquist sampling rate.

Ultrafast compressive imaging captures three-dimensional spatiotemporal information of transient events in a single shot. When a single-chirped optical probe is applied, the temporal information is obtained from the probe modulated in amplitude or phase using a direct frequency-time mapping method. Here, we extend the analysis of the temporal resolution of conventional one-dimensional ultrafast measurement techniques such as spectral interferometry to that in three-dimensional ultrafast compressive imaging. In this way, both the amplitude and phase of the probe are necessary for a full Fourier transform method, which obtains temporal information with an improved resolution determined by probe spectral bandwidth. The improved temporal resolution potentially enables ultrafast compressive imaging with an effective imaging speed at the quadrillion-frames-per-second level.

Temporal resolution of ultrafast compressive imaging using a single chirped optical probe

High harmonic generation (HHG) modulated by a weak laser field allows the perturbative wave mixing process which involves sum and difference frequency generations (SFG and DFG). The relative strengths of SFG and DFG have been extensively discussed in the literature but are still ambiguous. Here we experimentally study the relative strengths between SFG and DFG channels by applying a frequency-offset second-harmonic perturbing laser field collinearly in a thin gaseous nonlinear medium. It shows that SFG is favored for low harmonic orders, but DFG dominates for high-energy photons, when only short trajectories of high harmonics are considered. A semi-classical model incorporating both modulations to the tunneling ionization and the electron propagation steps by the perturbing laser field for a train of attosecond pulses explains the experimental results. 

Relative strengths of sum and difference frequency generation in perturbative high harmonic wave mixing

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