Imaging simulation and analysis of attitude jitter effect on topographic mapping for lunar orbiter stereo optical cameras

The geometric accuracy of topographic mapping with high-resolution remote sensing images is inevita-bly affected by the orbiter attitude jitter.Therefore,it is necessary to conduct preliminary research on the stereo mapping camera equipped on lunar orbiter before launching.In this work,an imaging simulation method consid-ering the attitude jitter is presented.The impact analysis of different attitude jitter on terrain undulation is conduct-ed by simulating jitter at three attitude angles,respectively.The proposed simulation method is based on the rigor-ous sensor model,using the lunar digital elevation model(DEM)and orthoimage as reference data.The orbit and attitude of the lunar stereo mapping camera are simulated while considering the attitude jitter.Two-dimensional simulated stereo images are generated according to the position and attitude of the orbiter in a given orbit.Experi-mental analyses were conducted by the DEM with the simulated stereo image.The simulation imaging results demonstrate that the proposed method can ensure imaging efficiency without losing the accuracy of topographic mapping.The effect of attitude jitter on the stereo mapping accuracy of the simulated images was analyzed through a DEM comparison.

Image Recognition Based on Deep Learning with Thermal Camera Sensing

As the COVID-19 epidemic spread across the globe,people around the world were advised or mandated to wear masks in public places to prevent its spreading further.In some cases,not wearing a mask could result in a fine.To monitor mask wearing,and to prevent the spread of future epidemics,this study proposes an image recognition system consisting of a camera,an infrared thermal array sensor,and a convolutional neural network trained in mask recognition.The infrared sensor monitors body temperature and displays the results in real-time on a liquid crystal display screen.The proposed system reduces the inefficiency of traditional object detection by providing training data according to the specific needs of the user and by applying You Only Look Once Version 4(YOLOv4)object detection technology,which experiments show has more efficient training parameters and a higher level of accuracy in object recognition.All datasets are uploaded to the cloud for storage using Google Colaboratory,saving human resources and achieving a high level of efficiency at a low cost.

Near-Infrared Imaging Using a High-Speed Monitoring Near Infrared Hyperspectral Camera(Compovision)

This review paper reports near-infrared(NIR)imaging studies using a newly-developed NIR camera,Compovision.Compovision can measure a significantly wide area of 150mm×250mm at high speed of between 2and 5s.It enables a wide spectral region measurement in the 1 000~2 350nm range at 6nm intervals.We investigated the potential of Compovision in the applications to industrial problems such as the evaluation of pharmaceutical tablets and polymers.Our studies have demonstrated that NIR imaging based on Compovision can solve several issues such as long acquisition times and relatively low sensitivity of detection.NIR imaging with Compovision is strongly expected to be applied not only to pharmaceutical tablet monitoring and polymer characterization but also to various applications such as those to food products,biomedical substances and organic and inorganic materials.

The Calibration of High-Speed Camera Imaging System for ELMs Observation on EAST Tokamak

A tangential fast visible camera has been set up in EAST tokamak for the study of edge MHD instabilities such as ELM. To determine the 3-D information from CCD images, Tsai＇s two-stage technique was utilized to calibrate the high-speed camera imaging system for ELM study. By applying tiles of the passive stabilizers in the tokamak device as the calibration pattern, transformation parameters for transforming from a 3-D world coordinate system to a 2-D image coordinate system were obtained, including the rotation matrix, the translation vector, the focal length and the lens distortion. The calibration errors were estimated and the results indicate the reliability of the method used for the camera imaging system. Through the calibration, some information about ELM filaments, such as positions and velocities were obtained from images of H-mode CCD videos.

GPU-accelerated three-dimensional reconstruction method of the Compton camera and its application in radionuclide imaging

A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.

Spatial resolution and image processing for pinhole camera-based X-ray fluorescence imaging: a simulation study

Spatial resolution and image-processing methods for full-field X-ray fluorescence(FF-XRF)imaging using X-ray pinhole cameras were studied using Geant4simulations with different geometries and algorithms for image reconstruction.The main objectives were:(1)calculating the quantum efficiency curves of specific cameras,(2)studying the relationships between the spatial resolution and the pinhole diameter,magnification,and camera binning value,and(3)comparing image-processing methods for pinhole camera systems.Several results were obtained using a point and plane source as the X-ray fluorescence emitter and an array of 100×100 silicon pixel detectors as the X-ray camera.The quantum efficiency of a back-illuminated deep depletion(BI-DD)structure was above 30%for the XRF energies in the 0.8–9 keV range,with the maximum of 93.7%at 4 keV.The best spatial resolution of the pinhole camera was 24.7μm and 31.3 lp/mm when measured using the profile function of the point source,with the diameter of 20μm,magnification of 3.16,and camera bin of 1.A blind deconvolution algorithm with Gaussian filtering performed better than the Wiener filter and Richardson iterative methods on FF-XRF images,with the signal-to-noise ratio of 7.81 dB and improved signalto-noise ratio of 7.24 dB at the diameter of 120μm,magnification of 1.0,and camera bin of 1.

Investigation of condition-induced bubble size and distribution in electroflotation using a high-speed camera

In the flotation process, bubble is a key factor in studying bubble-particle interaction and fine particle flo- tation. Knowledge on size distribution of bubbles in a flotation system is highly important. In this study, bubble distributions in different reagent concentrations, electrolyte concentrations, cathode apertures, and current densities in electroflotation are determined using a high-speed camera. Average bubble sizes under different conditions are calculated using Image-Pro@ Plus （Media Cybernetics@, MD, USA） and SigmaScan@ Pro （Systat Software, CA, USA） software. Results indicate that the average sizes of bubbles, which were generated through 38, 50, 74, 150, 250, 420, and 1000 μm cathode apertures, are 20.2, 29.5, 44.6, 59.2, 68.7, 78.5, and 88.8 μm, respectively. The optimal current density in electroflotation is 20 A/m2. Reagent and electrolyte concentrations, current density, and cathode aperture are important factors in controlling bubble size and nucleation. These factors also contribute to the control of fine- Particle flotation.

A Skeletal Camera Network for Close-range Images with a Data Driven Approach in Analyzing Stereo Configuration

Structure-from-Motion(SfM)techniques have been widely used for 3D geometry reconstruction from multi-view images.Nevertheless,the efficiency and quality of the reconstructed geometry depends on multiple factors,i.e.,the base-height ratio,intersection angle,overlap,and ground control points,etc.,which are rarely quantified in real-world applications.To answer this question,in this paper,we take a data-driven approach by analyzing hundreds of terrestrial stereo image configurations through a typical SfM algorithm.Two main meta-parameters with respect to base-height ratio and intersection angle are analyzed.Following the results,we propose a Skeletal Camera Network(SCN)and embed it into the SfM to lead to a novel SfM scheme called SCN-SfM,which limits tie-point matching to the remaining connected image pairs in SCN.The proposed method was applied in three terrestrial datasets.Experimental results have demonstrated the effectiveness of the proposed SCN-SfM to achieve 3D geometry with higher accuracy and fast time efficiency compared to the typical SfM method,whereas the completeness of the geometry is comparable.

Monocular Distance Estimated Based on PTZ Camera

This paper introduces an intelligent computational approach for extracting salient objects fromimages and estimatingtheir distance information with PTZ (Pan-Tilt-Zoom) cameras. PTZ cameras have found wide applications innumerous public places, serving various purposes such as public securitymanagement, natural disastermonitoring,and crisis alarms, particularly with the rapid development of Artificial Intelligence and global infrastructuralprojects. In this paper, we combine Gauss optical principles with the PTZ camera’s capabilities of horizontal andpitch rotation, as well as optical zoom, to estimate the distance of the object.We present a novel monocular objectdistance estimation model based on the Focal Length-Target Pixel Size (FLTPS) relationship, achieving an accuracyrate of over 95% for objects within a 5 km range. The salient object extraction is achieved through a simplifiedconvolution kernel and the utilization of the object’s RGB features, which offer significantly faster computingspeeds compared to Convolutional Neural Networks (CNNs). Additionally, we introduce the dark channel beforethe fog removal algorithm, resulting in a 20 dB increase in image definition, which significantly benefits distanceestimation. Our system offers the advantages of stability and low device load, making it an asset for public securityaffairs and providing a reference point for future developments in surveillance hardware.

A novel enhancement method for low illumination images based on microarray camera

It is difficult but important to get clear information from the low illumination images. In recent years the research of the low illumination image enhancement has become a hot topic in image processing and computer vision. The Retinex algorithm is one of the most popular methods in the field and uniform illumination is necessary to enhance low illumination image quality by using this algorithm. However, for the different areas of an image with contrast brightness differences, the illumination image is not smooth and causes halo artifacts so that it cannot retain the detail information of the original images. To solve the problem, we generalize the multi-scale Retinex algorithm and propose a new enhancement method for the low illumination images based on the microarray camera. The proposed method can well make up for the deficiency of imbalanced illumination and significantly inhibit the halo artifacts as well. Experimental results show that the proposed method can get better image enhancement effect compared to the multi-scale Retinex algorithm of a single image enhancement. Advantages of the method also include that it can significantly inhibit the halo artifacts and thus retain the details of the original images, it can improve the brightness and contrast of the image as well. The newly developed method in this paper has application potential to the images captured by pad and cell phone in the low illumination environment.

Image Motion Compensation of Off-Axis TMA Three-Line ArrayAerospace Mapping Cameras

To enhance the image motion compensation accuracy of off-axis three-mirror anastigmatic( TMA)three-line array aerospace mapping cameras,a new method of image motion velocity field modeling is proposed in this paper. Firstly,based on the imaging principle of mapping cameras,an analytical expression of image motion velocity of off-axis TMA three-line array aerospace mapping cameras is deduced from different coordinate systems we established and the attitude dynamics principle. Then,the case of a three-line array mapping camera is studied,in which the simulation of the focal plane image motion velocity fields of the forward-view camera,the nadir-view camera and the backward-view camera are carried out,and the optimization schemes for image motion velocity matching and drift angle matching are formulated according the simulation results. Finally,this method is verified with a dynamic imaging experimental system. The results are indicative of that when image motion compensation for nadir-view camera is conducted using the proposed image motion velocity field model,the line pair of target images at Nyquist frequency is clear and distinguishable. Under the constraint that modulation transfer function( MTF) reduces by 5%,when the horizontal frequencies of the forward-view camera and the backward-view camera are adjusted uniformly according to the proposed image motion velocity matching scheme,the time delay integration( TDI) stages reach 6 at most. When the TDI stages are more than 6,the three groups of camera will independently undergo horizontal frequency adjustment. However, when the proposed drift angle matching scheme is adopted for uniform drift angle adjustment,the number of TDI stages will not exceed 81. The experimental results have demonstrated the validity and accuracy of the proposed image motion velocity field model and matching optimization scheme,providing reliable basis for on-orbit image motion compensation of aerospace mapping cameras.

Particle velocity measurement of binary mixtures in the riser of a circulating fluidized bed by the combined use of electrostatic sensing and high-speed imaging

The flow dynamics of binary particle mixtures in the fluidized bed needs to be monitored in order to optimize the related industrial processes.In this paper,electrostatic sensing and high-speed imaging are applied to measure the velocities of polyethylene and sand particles in the binary particle mixtures in fluidization.Experimental studies were conducted on a lab-scale cold circulating fluidized bed.Correlation function between electrostatic signals from upstream and downstream electrodes placed along the riser shows two peaks that represent transit times for the two types of particles.To verify the above results,high-speed imaging was adopted to capture the flow images of particle mixtures.Particle Image Velocimetry and Particle Tracking Velocimetry algorithms were utilized to process the resulted images in order to measure the velocities of polyethylene and sand particles.The reasons for two-peak correlation functions are illustrated based on the frequency spectrums of the mono-solid-phase electrostatic signals and the velocity difference between polyethylene and sand particles.Finally,comparisons on the velocities obtained from electrostatic sensing and high-speed imaging demonstrate the electrostatic sensor can roughly estimate the particle velocity of binary particle mixtures in the near wall region of the circulating fluidized bed.

Leakage Currents of Zinc Oxide Surge Arresters in 22 kV Distribution System Using Thermal Image Camera

Zinc Oxide (ZnO) surge arresters (SAs) experience thermal runaway when the temperature exceeds the acceptable limit. This phenomenon is associated with the increase in resistive leakage current due to degradation. This paper presents the electrical performance of ZnO SAs in 22 kV distribution systems using thermal image camera under the power frequency AC operating voltages. When ZnO surge arresters are installation takes a long time in distribution system over more than 5 years. For the experimental study, as ZnO installation takes a long time over 6 years the leakage current is 63.9 mA, temperature differences were measured over a period of time over 14 degree Celsius. This data will be useful as a guideline for solving problems and reducing power loss from leakage current. Moreover, it will be useful in predicting lifetime of ZnO SAs.

Modeling Camera Image Formation Using a Feedforward Neural Network

One fundamental problem in computer vision and image processing is modeling the image formation of a camera, i.e., mapping a point in three-dimensional space to its projected position on the camera’s image plane. If the relationship between the space and the image plane is assumed to be linear, the relationship can be expressed in terms of a transfor-mation matrix and the matrix is often identified by regression. In this paper, we show that the space-to-image relation-ship in a camera can be modeled by a simple neural network. Unlike most other cases employing neural networks, the structure of the network is optimized so as for each link between neurons to have a physical meaning. This makes it possible to effectively initialize link weights and quickly train the network.

Research on black-and-white image processing method of smart car camera

In view of the images collection and processing problems of the smart car camera, the paper introduces a method which deals with field and line synchronization signal separation and binarization processing of the video signal collected from track fields, and which is capable to extract and position black border trajectory images effectively. According to the experiment results of the method, the camera images can be collected and processed effectively, and the accurate image information can be provided for the smart cars to travel along the track. The method has the advantages of being easy to use, strong adaptability, ideal performance and high practical value. On the basis of advantages the method is of high practical value in smart car races.

A New Method of Mosaicking Context Camera (CTX) Images for the Geomorphological Study of Martian Landscape

Various spacecraft and satellites from the world’s best space agencies are exploring Mars since 1970, constantly with great ability to capture the maximum amount of dataset for a better understanding of the red planet. In this paper, we propose a new method for making a mosaic of Mars Reconnaissance Orbiter (MRO) spacecraft payload Context Camera (CTX) images. In this procedure, we used ERDAS Imagine for image rectification and mosaicking as a tool for image processing, which is a new and unique method of generating a mosaic of thousands of CTX images to visualize the large-scale areas. The output product will be applicable for mapping of Martian geomorphological features, 2D mapping of the linear feature with high resolution, crater counting, and morphometric analysis to a certain extent.

Study on Focusing of Area Array Camera by Using Frequency of Images

Focusing of an area array camera is an important step in making a high precision imaging camera. Its testing method needs special study. In this paper, a method of camera focusing is introduced. The defocusing depth of camera is calculated by using the frequency spectrum of defocused image. This method is especially suitable for the focusing of the Planar Array Camera, and avoids the complicated work of adjusting the focus plane of the planar array camera in the focusing process.

Auto-registration and Orthorecification Algorithm for the Time Series HJ-1A/B CCD Images

How to deal with geometric distortion is an open problem when using the massive amount of satellite images at a national or global scale, especially for multi-temporal image analysis. In this paper, an algorithm is proposed to automatically rectify the geometric distortion of time-series CCD multi- spectral data of small constellation for environmental and disaster mitigation （HJ-1A/B） which was launched by China in 2008. In this algorithm, the area-based matching method was used to automatically search tie points firstly, and then the polynomial function was introduced to correct the systematic errors caused by the satellite motion along the roll, pitch and yaw direction. The improved orthorectification method was finally used to correct pixel displacement caused by off-nadir viewing of topography, which are random errors in the images and cannot be corrected by the polynomial equation. Nine scenes of level 2 HJ CCD images from one path/row were taken as the warp images to test the algorithm. The test result showed that the overall accuracy of the proposed algorithm was within 2 pixels （the average residuals were 37.8 m, and standard deviations were 19.8 m）. The accuracies of 45.96% validation points （VPs） were within 1 pixel and 90.33% VPs were within 2 pixels. The discussion showed that three main factors including the distortion patterns of HJ CCD images, pereent of cloud cover and the varying altitude of the satellite orbit may affect the search of tie points and the accuracy of results. Although the influence of varying altitude of the satellite orbits is less than the other factors, it is noted that detailed satellite altitude information should be given in the future to get a more precise result. The proposed algorithm should be an efficient tool for the geo-correction of HJ CCD multi-spectral images.

An Introduction to 2-CCD Digital Particle Image Velocimetry System and Its Application in Ocean Engineering

The basic principle of particle image velocinmetry (PIV) is described. When a PIV image is analyzed by the method of auto-correlation, there is a direction ambiguity of 180 degrees iii velocity measurement. The problem can be solved by using 'Image Shifting Technique', but this makes devices much complicated and difficult to control. A new arrangement of 2-CCD (Charge Coupled Device) fully digitized PIV system, which can also solve the problem successfully, is introduced in the paper. As an example of application of the system, an experimental result of flow field around a horizontal cylinder in wave is presented.

3D Motion Parameters Determination Based on Binocular Sequence Images

Exactly capturing three dimensional (3D) motion i nf ormation of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision s ystem and a method for determining 3D motion parameters of an object from binocu lar sequence images are introduced. The main steps include camera calibration, t he matching of motion and stereo images, 3D feature point correspondences and re solving the motion parameters. Finally, the experimental results of acquiring th e motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned meth od are presented.