Orthogonal transform based single-pixel imaging methods always improve the quality of recovered images, but they should take two-fold measurements of the illumination pattern the under full sampling. To decrease the number of measurements for time efficient imaging, we present a method that only uses the positive patterns to acquire measurement values and reconstruct images, the number of measurements can be reduced by 1/2. The robustness of the method is guaranteed by eliminating the random noise with the characteristics of orthogonal transform series. Simulation and experimental results based on discrete cosine transform single-pixel imaging, Hadamard transform single-pixel imaging and discrete W transform single-pixel imaging validate the effectiveness of the proposed method.

Traditional optical diffraction tomography (ODT) is limited by the numerical aperture of the objective lens, leading to the issue of ”missing cones.” This issue not only results in the underestimation of the refractive index of cells but also causes elongation of the refractive index distribution along the optical axis. Here, we propose a super-resolution microscopy imaging technology based on transport of intensity diffraction tomography (TIDT) with finite object support. It obtains three-dimensional (3D) intensity data stacks through an annular illumination system and directly reconstructs the three-dimensional refractive index distribution of the object using a deconvolution method. This avoids the inherent complexity of traditional ODT techniques, such as interferometric measurement procedures and mechanical beam scanning. Furthermore, by using the accurate identification of the sample’s geometric contour as prior information, super-resolution computation is performed using an optimized Gerchberg-Papoulis (GP) iterative algorithm, yielding high-quality three-dimensional rendered images. Our method effectively mitigates the problem of underestimating the refractive index of cells and significantly improves spatial resolution. By integrating three-dimensional rendering techniques based on VTK, the three-dimensional morphology of cells is clearly observed, providing an innovative solution for the development of three-dimensional microscopy imaging technologies.

We discuss the design and imaging features of a compact digital inline polarization holography system capable of singleshot extraction of complex amplitude information and polarization sensitive information corresponding to an anisotropic sample. The proposed method exploits the lens-less and compact design characteristics of the inline holographic system for the development of a quantitative polarization microscopy system. The quantitative imaging capability and measurement accuracy of the microscopy system is experimentally validated by single-shot detection of the digital polarization in-line holograms and the real-time extraction of full-field imaging features corresponding to standard birefringent targets and real-valued anisotropic samples.

Optical coherence microscopy is a promising method for visualization of the material refractive index, that is actively used for medical application. The implementation of the pump-probe scheme into optical coherence microscopy makes it possible to measure not only stationary quantities, but also to study the temporal dynamics of the optical properties changes of a sample under the optical pumping. In this work we demonstrate the possibility of the visualization of the refractive index modulation in semiconductor structures and estimation of the Q-factor of the excited resonances for lasing perovskite structure.

We have developed an AC magnetic field imaging system by combining an optically pumped magnetometer and a digital micromirror device. This system has been demonstrated to acquire distribution images representing the magnetic field generated by an electric current. We are investigating the application of this system to magnetic particle imaging for use in diagnostic applications. Particle signal generation requires an AC excitation field. Both the excitation field and the signal field from the particles are detected by the optically pumped magnetometer. They are analyzed using phase-sensitive detection with a lock-in amplifier. The resulting field images provides a clear indication of the positions of the particles.

Label-free microscopy that does not require the staining of weakly absorbing samples circumvent the adverse effects of exogenous dyes on the biological sample, and thus have received much attention in recent years. Among them, non-interferometric optical diffraction tomography microscopy has become a hot topic in the direction of label-free three-dimensional microscopy due to its system simplicity, ease of integration and independence from scattering noise. We recently designed a refractive index and fluorescence dual-modality microscopy system based on the transport of intensity diffraction tomography microscopy, which solves the absorption and phase information of the sample separately with the help of two illuminating apertures, and optimizes the imaging speed by applying an electrically tunable lens.

Rotating imaging optical satellites use the mode of cone scanning + area array to achieve high-temporal coverage of large areas, and the whole imaging process involves more loads and platform stand-alone machines, and its motion characteristics are mainly composed of camera load rotation, ground speed (satellite orbital motion + earth rotation), tremor disturbance, etc. The error sources involved in the imaging process mainly include GPS positioning error, pointing measurement mechanism (star sensor, gyroscope, pendulum mirror mechanism, fast reflection compensation mirror, detector rotation mechanism and turntable, etc.), camera load internal error, GPS receiver antenna and camera photography center eccentricity error, various load installation errors, time synchronization errors, etc. On-orbit geometric calibration is the key and basis for optical remote sensing satellite preprocessing. Affected by factors such as changes in the space environment during satellite launch and operation, the on-board payload structure and state will change, which will further lead to a large error between the laboratory calibration parameters and the real parameters after orbit, which will directly affect the accurate processing of image data and subsequent practical applications. Based on the strict geometric imaging model, this paper studies the analysis and calibration method of the full-link error characteristics of rotating ultra-wide optical satellite in motion, breaks through the key technologies such as analysis and simulation of the full-link error characteristics of dynamic imaging, construction of generalized equivalent normalized calibration model, and accurate calculation of error parameters based on step-by-step, so as to lay a foundation for the application of high-precision geometric processing and subsequent image stitching, fusion and classification monitoring of rotating imaging optical satellites.

Independent Component Analysis(ICA) applied in the field of image processing is a noval transformation domain method that utilizes sparse coding on the basis of analyzing the characteristics of the human visual system. It has multidirectionality, feature extraction, and edge modeling characteristics. Color transfer is currently the best way to integrate natural color in images. On the basis of effectively integrating ICA method and color transfer algorithm, a region texture color transfer-ICA natural color fusion algorithm is proposed by organically combining the matching parameters and transfer parameters of color transfer. Dynamic online method training ICA domain decomposition kernel function and synthesis kernel function; generating grayscale fusion images according to regional energy fusion rules; using grayscale image color transfer algorithm based on regional Gray Level Co-occurrence Matrix(GLCM) texture to extract texture features of reference images, achieving optimal matching with regional texture features of grayscale fusion images, and linearly assigning first-order and second-order color information to grayscale images to generate source color image; the Laplacian pyramid decomposes the color space channels of the source color image and color reference image into multiple resolutions for color transfer, enhancing the natural color fusion image’s representation of significant scene information such as local textures. Human visual perception and objective evaluation indicates that the fusion image highlights band features and enhances detailed information with natural and comfortable colors, further improving scene perception.

Spectral imaging, which integrates intricate spectral analysis with spatial data, is often limited by the cumbersome and costly nature of traditional spectral sensors that include complex mechanical parts. In this study, we tackle the precision issues in compact hyperspectral imaging through the creation of a broadband spectrometer using Ta2NiSe5/ReSe2 van der Waals heterostructures. This innovative design leverages drain-source voltage adjustments to modulate the spectral response, enabling the development of a highly compact spectrometer and hyperspectral imager that obviates the need for separate optical elements. Our findings underscore the potential of van der Waals heterostructures to redefine benchmarks for optical devices and substantially enhance hyperspectral imaging technology.

Organelles are highly dynamic and fulfill their function by constant motion and cooperation with each other. Current methods rely on fluorescence, leading to short observation time (via photobleaching) and experimental complexity (via multiple-labeling). While label-free microscopes promise a paradigm change in this regard, the spatiotemporal resolutions and specificity are still insufficient to study organelle interactions. Using mitochondria and lysosome as examples, the paper demonstrates that organelle-specific phase contrast microscopy (OS-PCM) can achieve automatic analysis of dynamic metrics of multiple organelles as well as their interactions from unlabeled cells for the first time. Compared to fluorescence-based methods, this method is gentle and holds great promise for label-free visualization and analysis of pan-organelle dynamics and interactions, with minimum perturbation to the cell.

Structured illumination microscopy (SIM) is one of the mainstream real-time super imaging techniques due to its fast temporal resolution, fluorescent probe compatibility, and low phototoxicity. However, in real-time imaging, parameter estimation and image reconstruction take a long time, making it impossible to observe image details in real time. To improve the imaging speed of the SIM system without losing spatial resolution, we introduced the Particle Swarm Optimization (PSO) method to estimate the illumination light parameters. By constructing a function with the same form as the cosine light and using the normalized cross-correlation (NCC) as the objective function, we initialize the parameter range and apply the PSO algorithm to perform parameter fitting within the specified range, comparing with the original image. Experimental results show that we can increase the reconstruction speed by approximately 2.5 times without affecting the reconstruction quality. The PSO algorithm achieves a good balance between temporal and spatial resolution in imaging.

The automobile hub plays a crucial role in supporting the weight of the entire vehicle and transmitting power, and the measurement accuracy of critical dimensions is closely related to the safe operation. A high-precision measurement method for critical dimensions of automobile hubs based on the minification projection segmentation algorithm is proposed in this paper. Firstly, the automobile hub point cloud captured by the structured light camera is preprocessed and the surface point cloud is extracted. Then, the cover end point cloud and the bolt hole point cloud are separated through the minification projection segmentation algorithm to calculate the critical dimensions of the automobile hub. Experimental results show that the detection accuracy of the critical dimensions using the method proposed in this paper can reach 100 microns.

With the rapid development of industrial manufacturing, three-dimensional measurement technology has become an effective method to acquire three-dimensional information of industrial products and to conduct defect inspection. When dealing with large-scale target objects like triangular hole panels, it is essential to collect point cloud data from various angles multiple times and register them together to construct a complete three- dimensional model. Prior to registration, preprocessing steps such as denoising the single-frame point cloud data are crucial in enhancing the quality of the point clouds and registration performance. In this paper, a specialized three-dimensional mask for denoising is presented, and the point cloud registration process is divided into two stages: a new coarse registration workflow based on the Rodrigues’ formula and an improved Trimmed ICP algorithm for fine registration. The effects of varied degrees of overlap on the accuracy and speed of point cloud registration are explored to guide data collection. Additionally, contour registration is utilized instead of full point cloud registration to improve efficiency. The experimental results indicate that the process designed in this paper can achieve high-precision point cloud registration quickly with only 25% overlap between two frames, achieving a precision of less than 50μm, which meets the stringent requirements of industrial applications.

Vascular calcification is a severe disease caused by dysregulated calcium-phosphate metabolism, influenced by factors such as genetics, aging, and chronic diseases, severely impacting vascular function. Vascular calcification inevitably leads to changes in vascular elasticity, which can be clearly reflected through elastography. However, existing elastography methods lack the resolution and sensitivity required for early-stage monitoring of vascular calcification. Thus, we propose a photoacoustic elastography method that combines optical and ultrasonic advantages, analyzing photoacoustic signals to obtain vascular elastic modulus and visualize calcification. This technology enables early detection of vascular calcification, providing crucial information for preventive and therapeutic strategies to reduce disease risk.

Optical diffraction tomography (ODT) is an innovative three-dimensional label-free microscopic imaging technique that offers high spatial resolution and low phototoxicity, making it suitable for long-term super-resolution 3D imaging of live cells. However, label-free results cannot specifically distinguish cellular structures. The main challenges in using AI models for digital staining are the lack of datasets and model generalization issues. This report presents a method for quickly and accurately creating label-free cell datasets and utilizes these datasets to train AI models capable of identifying various cellular structures such as cell membranes, nuclear membranes, nucleoli, lipid droplets, and mitochondria. The models achieved an accuracy of over 85% on target test sets.

Periodically poled lithium niobate (PPLN) is an optical crystal with excellent performance, featuring a large electro-optic coefficient and high nonlinear optical coefficient. Recently, several ultrahigh SHG and THG conversion efficiencies utilizing z-cut PPLN were demonstrated. To detect the domain structure of z-cut PPLN, the radially polarized light is used. This allows for enhanced domain wall detection signal in lithium niobate. We demonstrated that imaging using radially polarized light can achieve a contrast ratio of 0.83, which is only 0.71 for linearly polarized light. This technology is expected to pave the way for the promotion of integrated optical devices.

The conventional laser confocal microscopy achieves imaging of the three-dimensional volume region by establishing the conjugate relationship between the sample space and the image space, and through the three-dimensional motion of the sample. However, the movement of the sample stage not only reduces the imaging speed and introduces motion artifacts, but also limits the imaging samples to forms such as slices that are compatible with the sample holder, precluding in vivo three-dimensional imaging. In this study, by introducing phase control under end-to-end closed-loop control, precise and aberration-free all-optical three-dimensional high-speed scanning with high numerical aperture excitation is achieved. Without the need for sample movement, two-dimensional imaging at a kHz speed with 300 nm lateral resolution and a three-dimensional volume imaging speed in the hundreds of Hertz are realized, enabling in vivo real-time high-resolution three-dimensional imaging of research objects such as living mice in various life states.

In modern intelligent transportation, the weight and shape size of vehicle wheel are ones of the crucial fundamental quantities to ensure their conformity to design specifications serving a range of monitoring and management, from expressway inspection, and ship transportation to house applications. In this paper, an intelligent high-speed 3D geometric measuring system of vehicle wheel was developed based on optical imaging technologies. An automatic contour recognition algorithm of vehicle wheel was proposed. 3D geometric dimensional of wheel was described by a series of critical feature points in a virtual environment. At last, a series of experiments of several typical vehicle wheels have been performed to demonstrate this geometric measuring system and the final Intelligence level. This measuring system have been proven to be amenable for practical purposes through many tests so that it might be applicable to achieve vehicle wheels in a practical working environment.

Near-field optical characterization techniques are essential in nanophotonics research. Conventional methods typically rely on a nanoprobe for point-scanning the light field, which requires strict detection conditions and leads to long imaging durations.We present a novel near-field optical characterization system based on nonlinear effects. Using the nonlinear four-wave mixing effect, we can extract near-field polarizations through far-field imaging. This system features a broad field of view, scanning-less and real-time imaging capabilities, allowing for instantaneous characterization of evanescent fields like surface plasmon polaritons (SPPs). By employing a phase profile on a spatial light modulator (SLM), we can dynamically control the SPP field without nanostructures or nanofabrication. The scanning-less imaging simplifies nearfield characterization, achieving an image frame rate of about 5 frames per second with a standard CCD. This research aims to enhance the characterization of innovative structured light fields and improve understanding of light-structure interactions at the micro/nanoscale.

Object tracking algorithms based on traditional cameras exhibit poor performance under conditions of complex backgrounds or significant lighting variations, whereas event cameras, which feature high temporal resolution and wide dynamic range, can overcome these limitations. This paper proposes an efficient and fast tracking and localization algorithm based on event streams. To be specific, a novel event-based fast corner detection algorithm has been designed to perform in a highly efficient and timely manner in high-speed dynamic and low-light conditions. Finally, the extended Kalman filter is chosen as the primary method for estimating the target’s motion state, thereby accomplishing the task of target tracking based on event stream information. Comprehensive evaluation results demonstrate that the proposed algorithm achieves high tracking success rates and low average processing times in various scenarios involving high-speed single and multiple target tracking.

Innovative design, construction, and operating companies actively introduce building and structure information modeling (BIM) technologies into their production activities. Introducing these technologies makes it possible to improve the quality of design and construction and effectively optimize and reduce costs at the stages of construction and subsequent operation of a capital construction project. The article describes the problem of automating the operation processes of buildings and structures using information modeling technologies (BIM technologies). Several digital technological platforms for the operation of capital construction projects are considered, including solving the problem of monitoring the technical condition of buildings and structures.