Robust and adaptive star identification algorithm based on linear assignment for multiple large field of view visual imaging systems.

The integration of the visual imaging system and the self-attitude determination system in on-orbit space projects necessitates robust star identification algorithms. However, disturbances in the on-orbit environment pose a challenge to the accuracy and efficiency of star identification algorithms. This paper introduces a novel star identification algorithm, to the best of our knowledge, designed for multiple large field of view (FOV) visual imaging systems, providing stability in the presence of the noise types, including position noise, lost-star noise, and fake-star noise. We employ the dynamic simulated star images generation method to construct simulated star image libraries suitable for various cameras with different FOV angles. Our algorithm comprises two parts: the star edge matching for coarse matching of interstellar angular distances based on linear assignment, and the star point registration for precise matching of star vectors. This innovative combination of local edge generation and global matching approach achieves an impressive 97.83% identification accuracy, maintaining this performance even with a standard deviation of one pixel in image plane errors and up to five missing stars. A comprehensive approach involving both simulated and empirical experiments was employed to validate the algorithm's effectiveness. This integration of the visual imaging system and the self-attitude determination system offers potential benefits such as reduced space equipment weight, simplified satellite launch processes, and decreased maintenance costs.

Camera optimal projection model identification and calibration method based on the NGO-BA architecture.

In order to bridge the fundamental commonalities between imaging models of camera lenses with different principles and structures, allowing for an accurate description of imaging characteristics across a wide range of field-of-view (FOV), we have proposed a generic camera calibration method on the basis of the projection model optimization strategy. First, in order to cover the current mainstream projection models, piecewise functions for geometric projection models and a polynomial function for the fitting projection model are designed. Then, the corresponding camera multistation self-calibration bundle adjustment (BA) module is developed for various projection models. Further, by integrating the self-calibration BA algorithm into the northern goshawk optimization architecture, iterative optimization is performed on the projection model adjustment parameters, camera interior parameters, camera exterior parameters, and lens distortion parameters until the target reprojection (RP) error reaches the global minimum. The experimental results indicate that the calibration RP root mean square error in this method is 1/20 pixel for a 68° FOV camera, 1/13 pixel for an 84° FOV camera, 1/9 pixel for a 115° FOV camera, 1/9 pixel for a 135° FOV camera, and 1/6 pixel for a 180° FOV camera. This calibration method offers fast and versatile optimization for various projection model types, encompassing a wide range of projection functions. It can efficiently determine the optimal projection model and all imaging parameters for multiple cameras during the calibration process.

All-parameter calibration method of the on-orbit multi-view dynamic photogrammetry system.

Photogrammetry (PG) can present accurate data to evaluate the functional performance of large space structures. For camera calibration and orientation, the On-orbit Multi-view Dynamic Photogrammetry System (OMDPS) lacks appropriate spatial reference data. A multi-data fusion calibration method for all parameters for this kind of system is proposed in this paper as a solution to this issue. Firstly, a multi-camera relative position model is developed to solve the reference camera position unconstrained problem in the full-parameter calibration model of the OMDPS in accordance with the imaging model of stars and scale bar targets. Subsequently, the problem of adjustment failure and inaccurate adjustment in the multi-data fusion bundle adjustment is solved using the two-norm matrix and the weight matrix to adjust the Jacobian matrix with respect to all system parameters (e.g., camera interior parameters (CIP), camera exterior parameters (CEP), and lens distortion parameters (LDP)). Finally, all system parameters can be optimized simultaneously using this algorithm. In the actual data ground-based experiment, 333 spatial targets are measured using the V-star System (VS) and OMDPS. Taking the measurement of VS as the true value, the measurement results of OMDPS indicated that the in-plane Z-direction target coordinates root-mean-square error (RMSE) is less than 0.0538 mm and the Z-direction RMSE is less than 0.0428 mm. Out-of-plane Y-direction RMSE is less than 0.1514 mm. The application potential of the PG system for on-orbit measurement tasks is demonstrated through the actual data ground-based experiment.

Resonant-cavity-enhanced infrared detector incorporating an ultra-thin type-II superlattice: design and simulation.

A resonant-cavity-enhanced type-II superlattice (T2SL) infrared detector based on a metal grating has been designed to address the weak photon capture and low quantum efficiency (QE) issues of T2SL infrared detectors. Simulations have been conducted to analyze the effects of metal grating parameters, including length, thickness, and incident angle, on the spectral response and absorptivity of the absorption layers in T2SL infrared detectors. By optimizing the design, an appropriate resonant cavity structure was obtained. Research results indicate that the resonant cavity structure can significantly enhance the absorption rate of a T2SL infrared detector with a 0.2 µm thick absorption layer in the 3-5 µm wavelength range, observing peak absorption rates at 3.82 µm and 4.73 µm, with values of 97.6% and 98.2%, respectively. The absorption rate of the 0.2 µm thick T2SL absorption layer at peak wavelengths increased from 6.03% and 2.3% to 54.48% and 27.91%, respectively. The implementation of the resonant-cavity-enhanced T2SL infrared detector improves the QE while reducing absorption layer thickness, thus opening up new avenues for improving T2SL detector performance.

ECFuse: Edge-Consistent and Correlation-Driven Fusion Framework for Infrared and Visible Image Fusion.

Infrared and visible image fusion (IVIF) aims to render fused images that maintain the merits of both modalities. To tackle the challenge in fusing cross-modality information and avoiding texture loss in IVIF, we propose a novel edge-consistent and correlation-driven fusion framework (ECFuse). This framework leverages our proposed edge-consistency fusion module to maintain rich and coherent edges and textures, simultaneously introducing a correlation-driven deep learning network to fuse the cross-modality global features and modality-specific local features. Firstly, the framework employs a multi-scale transformation (MST) to decompose the source images into base and detail layers. Then, the edge-consistent fusion module fuses detail layers while maintaining the coherence of edges through consistency verification. A correlation-driven fusion network is proposed to fuse the base layers containing both modalities' main features in the transformation domain. Finally, the final fused spatial image is reconstructed by inverse MST. We conducted experiments to compare our ECFuse with both conventional and deep leaning approaches on TNO, LLVIP and M3FD datasets. The qualitative and quantitative evaluation results demonstrate the effectiveness of our framework. We also show that ECFuse can boost the performance in downstream infrared-visible object detection in a unified benchmark.

Modeling and simulation of all-optical diffractive neural network based on nonlinear optical materials.

In this Letter, we propose an all-optical diffractive deep neural network modeling method based on nonlinear optical materials. First, the nonlinear optical properties of graphene and zinc selenide (ZnSe) are analyzed. Then the optical limiting effect function corresponding to the saturation absorption coefficient of the nonlinear optical materials is fitted. The optical limiting effect function is taken as the nonlinear activation function of the neural network. Finally, the all-optical diffractive neural network model based on nonlinear materials is established. The numerical simulation results show that the model can effectively improve the nonlinear representation ability of the all-optical diffractive neural network. It provides a theoretical support for the further realization of a photonic artificial intelligence chip based on nonlinear optical materials.

Optical fiber shape sensing of polyimide skin for a flexible morphing wing: retraction.

The referenced article [Appl. Opt.56, 9325 (2017)APOPAI0003-693510.1364/AO.56.009325] has been retracted by the authors.

Long non-coding RNA MIR205HG regulates KRT17 and tumor processes in cervical cancer via interaction with SRSF1.

Abnormal expression of long non-coding RNAs (lncRNAs) has been demonstrated to be a vital regulatory factor in a large number of malignancies. The investigation in cervical cancer and the associated modulation mechanisms are yet to be probed. The aim of this study is to specifically investigate the expression pattern and modulatory mechanism of MIR205HG in cervical cancer. Our paper firstly revealed the up-regulation of KRT17 in cervical cancer. Function assays further displayed that KRT17 silencing impaired the proliferation and migration, and activated the apoptosis of cervical cancer cells. Based on the finding that MIR205HG could regulate KRT17 expression, we further probed the detailed mechanism between MIR205HG and KRT17. It was observed from mechanism experiments that MIR205HG depleted SRSF1 to increase KRT17 expression. The whole mechanism of MIR205HG/SRSF1/KRT17 axis affecting cell proliferation, apoptosis and migration in cervical cancer was validated using rescue assays. In conclusion, MIR205HG modulated the biological activities of cervical cancer cells via targeting SRSF1 and regulating KRT17, which better understood the pathogenesis of cervical carcinoma and excavated a novel therapeutic target.

Characterization of metallic-packaging fiber Bragg grating sensors with coated and bare fibers.

Metallic packaging of fiber Bragg grating (FBG) sensors is developed using the ultrasonic welding method. Both polyimide-coated fiber and bare fiber could be bonded well to aluminum alloy substrate using Sn-Bi alloy. Two kinds of metal-packaged FBG sensors, coated FBG and bare FBG, are characterized for studying the thermal sensitivity, strain response, short-term creep, and temporal temperature response. Both FBG sensors showed increasing sensitivity with temperature from -40°C to 80°C. The metal-packaged coated FBG sensor displayed relative strengths in strain stability, repeatability, creep, spectra shape, and temperature response when compared with the bare one. Moreover, the boundaries between optical fiber and metal alloy are intact, and cross-sectional scanning electron microscope micrographs clearly illustrated that metal alloy coated well with the coated and bare fiber.

Microdeformation of RBCs under oxidative stress measured by digital holographic microscopy and optical tweezers.

This paper utilized digital holographic microscopy and optical tweezers to study microdeformation of red blood cells (RBCs) dynamically under oxidative stress. RBCs attached with microbeads were stretched by dual optical tweezers to generate microdeformation. Morphology of RBCs under manipulation were recorded dynamically and recovered by off-axis digital holographic microscopy method. RBCs treated with H2O2 at different concentrations were measured to investigate the mechanical properties under oxidative stress. Use of optical tweezers and off-axis digital holographic microscopy enhanced measuring accuracy compared with the traditional method. Microdeformation of RBCs is also more consistent with the physiological situation. This proposal is meaningful for clinical applications and basic analysis of Parkinson's disease research.

A metal-organic zeolitic framework with immobilized urease for use in a tapered optical fiber urea biosensor.

A tapered single-mode coreless single-mode (SCS) structure with high sensitivity for sensing refractive index is described. In order to achieve high specificity of optical biosensors, here enzyme capsulation film was achieved by embedding urease in zeolitic imidazolate framework (ZIF-8/urease) through in situ growth approach on the coreless fibers. Determination of urea is achieved through online monitoring of its binding to the urease in zeolitic imidazolate framework. Refractive index change result in wavelength shifts of the optical fiber biosensor. The resonance wavelength exhibits a good linear relationship with urea concentration in the range of 1 to 10 mM with detection limit of 0.1 mM and sensitivity of 0.8 mM/RIU (refractive index unit) if operated with broadband light ranging from 1525 nm to 1590 nm. Final assessment of optical biosensor in real sample was performed where excellent performance in terms of sensitivity and selectivity was observed. Schematic representation of experimental setup and mechanism for urea detection. A tapered single-mode coreless single-mode (SCS) structure is placed between a broadband light source ranging (BBS) and optical spectrum analyzer (OSA). ZIF-8/urease composites are applied as a recognition layer for urea detection.

Optical Fiber Sensor Performance Evaluation in Soft Polyimide Film with Different Thickness Ratios.

To meet the application requirements of curvature measurement for soft biomedical robotics and flexible morphing wings of aircraft, the optical fiber Bragg grating (FBG) shape sensor for soft robots and flexible morphing wing was implemented. This optical FBG is embedded in polyimide film and then fixed in the body of a soft robot and morphing wing. However, a lack of analysis on the embedded depth of FBG sensors in polyimide film and its sensitivity greatly limits their application potential. Herein, the relationship between the embedded depth of the FBG sensor in polyimide film and its sensitivity and stability are investigated. The sensing principle and structural design of the FBG sensor embedded in polyimide film are introduced; the bending curvatures of the FBG sensor and its wavelength shift in polyimide film are studied; and the relationship between the sensitivity, stability, and embedded depth of these sensors are verified experimentally. The results showed that wavelength shift and curvature have a linear relationship. With the sensor's curvature ranging from 0 m-1 to 30 m-1, their maximum sensitivity is 50.65 pm/m-1, and their minimum sensitivity is 1.96 pm/m-1. The designed FBG sensor embedded in polyimide films shows good consistency in repeated experiments for soft actuator and morphing wing measurement; the FBG sensing method therefore has potential for real applications in shape monitoring in the fields of soft robotics and the flexible morphing wings of aircraft.

Non-contact temperature-independent random-displacement sensor using two fiber Bragg gratings.

We present a full-range displacement sensor system using two fiber Bragg gratings (FBGs). The magnetic-scale-combined FBGs allow the exploration of random position. The sinusoidal function variations are displayed by two detectors with a phase difference of 90 deg, and the optimal magnetic gap is explored through numerical simulations. The feasibility of the method is demonstrated in experiments that show the sinusoidal relation between center wavelength shifts with the linear displacement. Results showed that the amplitudes of the tensile-compressive load were 446.1 µÏµ and 434.7 µÏµ, respectively, with linearity of 0.998 and 0.999 at 1.5 mm between the detector and the magnetic scale. These results demonstrate that the sensors can realize non-contact, temperature-independent and full-range measurement.

Simultaneous Robot⁻World and Hand⁻Eye Calibration without a Calibration Object.

An extended robot⁻world and hand⁻eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot⁻world and hand⁻eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

Analysis of Flow Cytometric Fluorescence Lifetime with Time-Delay Estimation of Pulse Signals.

The measurement of fluorescence lifetimes emerged in flow cytometry because it is not impacted by the non-linearity, which occurs in fluorescence intensity measurements. However, this significantly increases the cost and complexity of a traditional flow cytometer. This work reports a simple method of fluorescence lifetime measurement of a flow cytometer based on the cytometric fluorescence pulse time-delay estimation and hardware time-delay calibration. The modified chirp Z-transform (MCZT) algorithm, combined with the algorithm of fine interpolation of correlation peak (FICP), is applied to improve the temporal resolution of the cross-correlation function of the scattering and fluorescence signals, which in turn improves the time-delay estimation accuracy. The estimation accuracy is verified by Gauss fitting. Cells that were labeled simultaneously with three-color reagents are measured; the statistical results of 5000 cells are compared with reference values and are verified with the pulse width variation. The results show the potential of fluorescence lifetime measurements in the traditional flow cytometer.

Simultaneous All-Parameters Calibration and Assessment of a Stereo Camera Pair Using a Scale Bar.

Highly accurate and easy-to-operate calibration (to determine the interior and distortion parameters) and orientation (to determine the exterior parameters) methods for cameras in large volume is a very important topic for expanding the application scope of 3D vision and photogrammetry techniques. This paper proposes a method for simultaneously calibrating, orienting and assessing multi-camera 3D measurement systems in large measurement volume scenarios. The primary idea is building 3D point and length arrays by moving a scale bar in the measurement volume and then conducting a self-calibrating bundle adjustment that involves all the image points and lengths of both cameras. Relative exterior parameters between the camera pair are estimated by the five point relative orientation method. The interior, distortion parameters of each camera and the relative exterior parameters are optimized through bundle adjustment of the network geometry that is strengthened through applying the distance constraints. This method provides both internal precision and external accuracy assessment of the calibration performance. Simulations and real data experiments are designed and conducted to validate the effectivity of the method and analyze its performance under different network geometries. The RMSE of length measurement is less than 0.25 mm and the relative precision is higher than 1/25,000 for a two camera system calibrated by the proposed method in a volume of 12 m × 8 m × 4 m. Compared with the state-of-the-art point array self-calibrating bundle adjustment method, the proposed method is easier to operate and can significantly reduce systematic errors caused by wrong scaling.

Modelling and calibration of depth-dependent distortion for large depth visual measurement cameras.

Lens distortion parameters vary with the distance between the object point and the image plane. We propose an analytical model of depth-dependent distortion for large depth-of-field digital cameras used for high accuracy photogrammetry. Compared with the magnification-dependent model, the proposed one does not need focusing operation during calibration, thus eliminates focusing errors and guarantees the stability of camera interior parameters. Compared with the widely used constant distortion parameter model, the proposed model reduces the maximum distortion variation from 8.0 µm to 0.9 µm at 20 mm radial distance when the depth changes from 2.46 m to 4.51 m for the 35 mm lens, and from 23.0 µm to 3.6 µm when the depth changes from 2.07 m to 4.17 m for the 50 mm lens. Additionally, when applied to photogrammetry bundle adjustment, the proposed model reduces length measurement standard deviation from 0.055 mm to 0.028 mm in a measurement volume of 7.0 m × 3.5 m × 2.5m compared with the constant parameter model.

Optical fiber shape sensing of polyimide skin for a flexible morphing wing.

This paper presents the 3D shape sensing of polyimide thin film skin for a flexible morphing wing using fiber Bragg grating (FBG) sensors. The calibration curves of the FBG sensors are measured experimentally to ensure relative accurate conversion between Bragg wavelength shift (BWS) and bending curvature of the polyimide skin. The reflection spectra of the FBG sensors are measured at different airfoil profiles, and the variation tendency of the BWS values with the airfoil profiles are analyzed. The bending curvatures of the polyimide thin film skin at different airfoil profiles are calculated using the measured BWS values of the FBG sensors and the linear interpolation algorithm. The 3D shapes of the polyimide skin at different airfoil profiles are reconstructed based on the measured bending curvatures and the interpolation and curve fitting functions. The 3D precise visual measurements are conducted using a digital photogrammetry system, and then the correctness of the shape reconstruction results are verified. The results prove that the maximum error between the 3D visual and FBG measurements is less than 5%. The FBG sensing method is effective for the shape sensing of polyimide skin for flexible morphing wing.

[Cell data clustering method in flow cytometry based on kernel principal component analysis].

The process of multi-parametric flow cytometry data analysis is complicate and time-consuming,which requires well-trained professionals to operate on. To overcome this limitation, a method for multi-parameter flow cytometry data processing based on kernel principal component analysis(KPCA) was proposed in this paper. The dimensionality of the data was reduced by nonlinear transform. After the new characteristic variables were obtained,automatical clustering can be achieved using improved K-means algorithm. Experimental data of peripheral blood lymphocyte were processed using the principal component analysis(PCA)-based method and KPCA-based method and then the influence of different feature parameter selections was explored. The results indicate that the KPCA can be successfully applied in the multi-parameter flow cytometry data analysis for efficient and accurate cell clustering, which can improve the efficiency of flow cytometry in clinical diagnosis analysis.