Charge-coupled Device Imaging Research Articles

Investigation of the expansion dynamics of silicon plasmas generated by double nanosecond laser pulses

A systematic investigation of the expansion dynamics of plasma plumes generated by two Q-switched Nd:YAG lasers at 1064 nm wavelength operating on a silicon target was undertaken for the inter-pulse delay times of 0, 100, 200, and 400 ns using a technique involving fast-gated intensified charge-coupled device imaging. Our results indicate that the plasmas exhibit free expansion in a vacuum environment at an inter-pulse delay time of 0 ns. With increasing inter-pulse delay time, the plasma front becomes sharpened and an interaction boundary is formed. Moreover, using the radiation intensity distribution along the plasma axis of symmetry, the formation and evolution mechanism of the plasmas generated by the double pulses was analyzed at different inter-pulse delay times. Finally, the experimental results of the expansion of the plasma core and front were compared with a radiation hydrodynamics model and a drag model, and were found to be generally in good agreement.

A High-Speed Imaging Method Based on Compressive Sensing for Sound Extraction Using a Low-Speed Camera.

This paper reports an efficient method for sound extraction from high-speed light spot videos reconstructed from the coded light spot images captured with a low-speed camera based on compressive sensing, but at the expense of consuming time. The proposed method first gets the high-speed video of the light spot that is illuminated on the vibrating target caused by sound. Then the centroid of the light spot is used to recover the sound. Simulations of the proposed method are carried out and experimental results are demonstrated. The results show that high-speed videos with a frame rate of 2000 Hz can be reconstructed with a low-speed (100 Hz) charge-coupled device (CCD) camera, which is randomly modulated by a digital micro-mirror device (DMD) 20 times during each exposure time. This means a speed improvement of 20 times is achieved. The effects of synchronization between CCD image recording and DMD modulation, the optimal sampling patterns of DMD, and sound vibration amplitudes on the performance of the proposed method are evaluated. Using this compressive camera, speech (counting from one to four in Chinese) was recovered well. This has been confirmed by directly listening to the recovered sound, and the intelligibility value (0–1) that evaluated the similarity between them was 0.8185. Although we use this compressive camera for sound detection, we expect it to be useful in applications related to vibration and motion.

Histological Evaluation of the Healing Process of Various Bone Graft Materials after Engraftment into the Human Body.

The purpose of this study was to measure the level of new bone formation induced by various bone graft materials to provide clinicians with more choices. The samples were divided into three groups: group 1 (n = 9: allograft + xenograft, DBX®, San Francisco, CA, USA + Bio-Oss®, Princeton, NJ, USA), group 2 (n = 10: xenograft, Bio-Oss®), and group 3 (n = 8: autogenous tooth bone graft, AutoBT®, Korea Tooth Bank, Seoul, Korea). The average duration of evaluation was 9.56, 2.50, and 3.38 months, respectively. A tissue sample was taken from 27 patients during the second implant surgery. New bone formation was measured via histomorphometry, using a charge-coupled device camera, adaptor, and image analysis software. Total bone area, total area, and ((total bone area/total area) × 100) was measured to determine the extent of new bone formation. The mean value of the total bone area was 152,232.63 μm2; the mean value of the total area was 1,153,696.46 μm2; and the mean total bone area/total area ratio was 13.50%. In each comparison, there was no significant difference among the groups; no inflammation or complications were found in any of the groups. AutoBT®, an autogenous tooth bone graft, resulted in a level of bone formation similar to that using allografts and xenografts.

Growth and Brilliant Photo-Emission of Crystalline Hexagonal Column of Alq₃ Microwires.

We report the growth and nanoscale luminescence characteristics of 8-hydroxyquinolinato aluminum (Alq3) with a crystalline hexagonal column morphology. Pristine Alq3 nanoparticles (NPs) were prepared using a conventional reprecipitation method. Crystal hexagonal columns of Alq3 were grown by using a surfactant-assisted self-assembly technique as an adjunct to the aforementioned reprecipitation method. The formation and structural properties of the crystalline and non-crystalline Alq3 NPs were analyzed with scanning electron microscopy and X-ray diffraction. The nanoscale photoluminescence (PL) characteristics and the luminescence color of the Alq3 single NPs and their crystal microwires (MWs) were evaluated from color charge-coupled device images acquired using a high-resolution laser confocal microscope. In comparison with the Alq3 NPs, the crystalline MWs exhibited a very bright and sharp emission. This enhanced and sharp emission from the crystalline Alq3 single MWs originated from effective π-π stacking of the Alq3 molecules due to strong interactions in the crystalline structure.

Application of an image fusion algorithm in measuring the laser beam far-field divergence angle

The measurement of laser beam far-field parameters plays an important role in the accurate assessment of the laser’s transmission effect and the laser system’s overall performance. A simpler and more convenient detection method for an image fusion algorithm of saturated and unsaturated double frames is proposed, based on the technology of image fusion, to measure the laser beam far-field angle. After being attenuated by the attenuating plate, the pulsed laser is focused by the objective lens to form a spot image on the charge-coupled device image plane. The spot size that has been attenuated by the attenuator can be calculated and analyzed by the mathematical modeling software MATLAB, and then the far-field divergence angle value is calculated. The experimental device and the working principle are introduced in detail, theoretical analysis of the computer data processing method is given, and the data processing results are shown in the end. Experimental results indicate that the amount of computation compared with the previous image fusion algorithm is smaller, this method can be used to measure the laser beam far-field divergence angle, the calculation speed is fast, and the measurement accuracy can be up to 2%.

Luciferase Complementation Assay for Protein‐Protein Interactions in Plants

Constitutive and dynamic protein-protein interactions are fundamental to all aspects of cellular processes. Compared to other techniques measuring protein-protein interactions in plants, the luciferase complementation assay has a number of advantages: it detects plant protein-protein interactions in real time, requires little hands-on manipulation of samples, is highly quantitative, has extremely low background, and can be easily scaled up for high-throughput interactome studies. Here, we describe a protocol that includes two alternate data collection methods to quantify luminescence results based on Agrobacterium-mediated transient luciferase expression in Nicotiana benthamiana. One data collection method employs a charge-coupled device imaging system that allows the interactions to be presented as images, and the other employs a luminometer, which enables the assay to be conducted in a 96-well plate. Technical parameters related to frequently encountered problems and common errors, presented here, are important for performing this assay successfully. © 2018 by John Wiley & Sons, Inc.

Topographic surface roughness analysis based on image processing of terrestrial planet

We discuss a roughness problems in this paper. Roughness measurements play a fundamental role in terrestrial planet research. The main question discussed in this paper is how to build a more efficient roughness model on the basis of images. The model needs to beat a series of traditional roughness problems on the image. Lunar reconnaissance orbiter camera (LROc) and charged coupled device (CCD) images are our primary data target. Roughness is divided into trend surface roughness and topography roughness with analysis and inversion. The two parts are combined and analyzed. The analysis is based on two structural features: trend reflection and detail details surface. Our team use inversion to remap the surface roughness by CCD image, and then classify the roughness into the trend influence class and the detail influence class. We use frequency analysis tools are to find the discontinuous energy in the frequency domain. Finally, these roughness information are remapped into a visual image results. Our model provide a more accurate method on terrestrial planetary surface roughness problem. We can analyze the difference between the trend surface and the detail roughness by single image. We find that, lunar surface roughness presents more detail with the help of the frequency analysis. Highlands and the mare shows very different roughness decomposition. Our analysis shows better results in the areas in which details surface is not associated with roughness. It is hoped that this study will provide new insights in the surface roughness of terrestrial planets. Especially for CCD images (LROc) rather than details surface data (DEM). In the future, we will focus on calculations and analysis for Mars based on the mode in this paper. For the roughness data, we will start depth learning, classification, pattern recognition and other research in future work.

Distinguishing two phenotypes of blooms using the normalised difference peak-valley index (NDPI) and Cyano-Chlorophyta index (CCI)

Harmful algal blooms are now widely recognised as a severe threat to freshwater ecosystems, particularly in semi-fluvial environments created by river damming. Given the high spatial and temporal variability of cyanobacterial blooms, remote sensing is more suitable than conventional field surveys in monitoring blooms. However, the majority of existing algorithms cannot distinguish cyanobacterial blooms from eukaryotic algal blooms by extracting spectral features in the remote-sensing reflectance (Rrs). In this study, in situ Rrs spectra of cyanobacterial and green algal blooms in Lakes Gaoyang, Hanfeng and Changshou of the Three Gorges Reservoir (TGR) in China were recorded. Characteristic spectral indices, namely, the normalised difference peak-valley index and Cyano-Chlorophyta index, were used to develop an algorithm that can effectively distinguish cyanobacterial and green algal blooms. The proposed algorithm was also used to investigate the spatio–temporal dynamics of the two phenotypes of blooms derived from Huan Jing 1 charge-coupled device images. The resulting accuracy of 93.5% demonstrated that remote sensing technology, in conjunction with field observation, could efficiently differentiate bloom-forming species and assess the water quality in the TGR.

Lens implementation on the GATE Monte Carlo toolkit for optical imaging simulation

Optical imaging techniques are widely used for in vivo preclinical studies, and it is well known that the Geant4 Application for Emission Tomography (GATE) can be employed for the Monte Carlo (MC) modeling of light transport inside heterogeneous tissues. However, the GATE MC toolkit is limited in that it does not yet include optical lens implementation, even though this is required for a more realistic optical imaging simulation. We describe our implementation of a biconvex lens into the GATE MC toolkit to improve both the sensitivity and spatial resolution for optical imaging simulation. The lens implemented into the GATE was validated against the ZEMAX optical simulation using an US air force 1951 resolution target. The ray diagrams and the charge-coupled device images of the GATE optical simulation agreed with the ZEMAX optical simulation results. In conclusion, the use of a lens on the GATE optical simulation could improve the image quality of bioluminescence and fluorescence significantly as compared with pinhole optics.

An improved adaptive preprocessing method for TDI CCD images

In order to achieve high quality images with time-delayed integration (TDI) charge-coupled device (CCD) imaging system, an improved adaptive preprocessing method is proposed with functions of both denoising and edge enhancement. It is a weighted average filter integrating the average filter and the improved range filter. The weighted factors are deduced in terms of a cost function, which are adjustable to different images. To validate the proposed method, extensive tests are carried out on a developed TDI CCD imaging system. The experimental results confirm that this preprocessing method can fulfill the noise removal and edge sharpening simultaneously, which can play an important role in remote sensing field.

Investigating artifacts associated with β-particle interactions in charge-coupled devices

Charge-coupled devices (CCDs) show potential for detecting charged particles and ionizing radiation. In particular, the clusters in the pixel images produced can be distinctive for [Formula: see text] and [Formula: see text] radiation, with [Formula: see text] particles causing symmetrical clusters or vertical tracks, and [Formula: see text] particles causing long, curved tracks. This distinction may be exploited by means of a handheld, portable device for in-situ detection, and identification of radioactive contamination. [Formula: see text]-particle track interactions in CCDs have been investigated. Simulative results using CASINO (Monte Carlo Simulation of Electron Trajectory in Solids) attempt to predict the size of [Formula: see text]-particle pixel clusters, using 512 keV and 310 keV electrons to represent [Formula: see text]Cs and [Formula: see text]Co, respectively. The number of pixels that higher-energy electrons traversed peaked at two, while lower-energy electrons had a smaller peak of 2.5 pixels, with a higher proportion of large cluster sizes. This finding is consistent with the higher scattering cross-section for lower-energy [Formula: see text] particles. By contrast, experimental data show a peak at one pixel for both sources, owing to the addition of smaller [Formula: see text] clusters. The [Formula: see text]Co source shows a higher proportion of large cluster sizes than the [Formula: see text]Cs, as was also seen in the simulation; however, the difference was small, as these sources are similar in energy. Simulative and experimental data will be used to process the CCD images further, with the objective of distinguishing between [Formula: see text] and [Formula: see text] radiation. Investigations have also been carried out using a [Formula: see text]Po [Formula: see text] particle source. Horizontal streaks were seen in the images produced, with an average length of 14 pixels. Further research will be performed using an accelerator to obtain different [Formula: see text]-particle energies.

Vertical Accuracy Simulation of Stereo Mapping Using a Small Matrix Charge-Coupled Device

At present, without ground control points (GCPs), the positioning accuracy of remote sensing images often fails to meet the growing requirements for mapping accuracy. Multi-load synergy to improve accuracy without GCPs by eliminating the impact of stereo accuracy, which is caused by on-orbit measurement error, is urgently needed to improve large-scale mapping. In this study, we analyzed error sources in stereo imaging mode and found that vertical accuracy depends on the relative accuracy of attitude during symmetric stereoscopic mapping. With the assistance of small matrix charge-coupled device (CCD) images and the block adjustment method, relative accuracy of attitude was improved, allowing for the improvement in vertical accuracy without GCPs. The simulation results show that vertical accuracy in symmetric stereo mode is not affected by attitude system error. After the restoration of imaging attitude processed by a sequence of matrix CCD images, the relative accuracy of the attitude increased, and the accuracy of the elevation without GCPs improved significantly. The results demonstrate the feasibility of small matrix CCD-assisted stereo mapping.

Measurement of Dynamic Deflection of Large-Span Bridges with Charge Coupled Device Image Detection System

Measurement of Dynamic Deflection of Large-Span Bridges with Charge Coupled Device Image Detection System

A Denoising Method for Randomly Clustered Noise in ICCD Sensing Images Based on Hypergraph Cut and Down Sampling.

Intensified charge-coupled device (ICCD) images are captured by ICCD sensors in extremely low-light conditions. They often contains spatially clustered noises and general filtering methods do not work well. We find that the scale of the clustered noise in ICCD sensing images is often much smaller than that of the true structural information. Then the clustered noise can be identified by properly down-sampling and then up-sampling the ICCD sensing image and comparing it to the noisy image. Based on this finding, we present a denoising algorithm to remove the randomly clustered noise in ICCD images. First, we over-segment the ICCD image into a set of flat patches, and each patch contains very little structural information. Second, we classify the patches into noisy patches and noise-free patches based on the hypergraph cut method. Then the noise-free patches are easily recovered by the general block-matching and 3D filtering (BM3D) algorithm, since they often do not contain the clustered noise. The noisy patches are recovered by subtracting the identified clustered noise from the noisy patches. After that, we could get the whole recovered ICCD image. Finally, the quality of the recovered ICCD image is further improved by diminishing the remaining sparse noise with robust principal component analysis. Experiments are conducted on a set of ICCD images and compared with four existing denoising algorithms, which shows that the proposed algorithm removes well the randomly clustered noise and preserves the true textural information in the ICCD sensing images.

Forest Types Classification Based on Multi-Source Data Fusion

Forest plays an important role in global carbon, hydrological and atmospheric cycles and provides a wide range of valuable ecosystem services. Timely and accurate forest-type mapping is an essential topic for forest resource inventory supporting forest management, conservation biology and ecological restoration. Despite efforts and progress having been made in forest cover mapping using multi-source remotely sensed data, fine spatial, temporal and spectral resolution modeling for forest type distinction is still limited. In this paper, we proposed a novel spatial-temporal-spectral fusion framework through spatial-spectral fusion and spatial-temporal fusion. Addressing the shortcomings of the commonly-used spatial-spectral fusion model, we proposed a novel spatial-spectral fusion model called the Segmented Difference Value method (SEGDV) to generate fine spatial-spectra-resolution images by blending the China environment 1A series satellite (HJ-1A) multispectral image (Charge Coupled Device (CCD)) and Hyperspectral Imager (HSI). A Hierarchical Spatiotemporal Adaptive Fusion Model (HSTAFM) was used to conduct spatial-temporal fusion to generate the fine spatial-temporal-resolution image by blending the HJ-1A CCD and Moderate Resolution Imaging Spectroradiometer (MODIS) data. The spatial-spectral-temporal information was utilized simultaneously to distinguish various forest types. Experimental results of the classification comparison conducted in the Gan River source nature reserves showed that the proposed method could enhance spatial, temporal and spectral information effectively, and the fused dataset yielded the highest classification accuracy of 83.6% compared with the classification results derived from single Landsat-8 (69.95%), single spatial-spectral fusion (70.95%) and single spatial-temporal fusion (78.94%) images, thereby indicating that the proposed method could be valid and applicable in forest type classification.

Actuation of a lean-premixed flame by diffuse non-equilibrium nanosecond-pulsed plasma at atmospheric pressure

This study investigates the effect of diffuse non-equilibrium nanosecond-pulsed plasma at atmospheric pressure on a lean-premixed CH4-air flame (ϕ = 0.65, P ∼ 0.3 kW). The domain of diffuse plasma existence is explored for both the case of the cold flow (no flame) and the case where a flame is stabilized downstream. The dynamics of plasma propagation and the flame displacement, following a high-voltage pulse, were measured using intensified charge-coupled device imaging. The energy of the plasma was measured using electrical probes and measurements of the second positive system of nitrogen were used to determine the rotational temperature and vibrational populations in the plasma. The effect of plasma on a flame was investigated by varying the pulse repetition frequency gradually from 1 to 7 kHz. Time-resolved imaging of the plasma emission shows that the primary streamer travels at higher velocities with increased pulsing frequency and with the presence of a flame ignited downstream of the discharge. Time-resolved imaging of the flame, following a high-voltage pulse, shows that the flame moves upstream into the unburned methane-air mixture with increased pulsing frequency. As the flame is displaced upstream, the nature of the discharge also changes, whereby less energy is coupled to the gas volume. Spectroscopic results reveal that the region in which the flame stabilizes is that of highest vibrational excitation and lowest rotational temperature. This actuation method is evidence of low-temperature chemical flame enhancement and potential control of a lean-premixed laminar flame at atmospheric pressure.

$\gamma $ -Ray Detection Using Commercial Off-the-Shelf CMOS and CCD Image Sensors

In this paper, we present the results of research on the response of four types of commercial off-the-shelf (COTS), CMOS, and charge-coupled device (CCD) image sensors to $\gamma $ photons. The aim of this paper was to study the potential use of CCD and CMOS COTS image sensors as $\gamma $ -ray detectors. A 60Co $\gamma $ source was used to study the response behavior of the sensors to the irradiant photons. The results show that the CMOS image sensors have much less background noise before irradiation and have better radiation resistance below 51.24 Gy. The background noise of CCD sensors obviously increases with a larger total ionizing dose. The linearity of the dose-rate response of CCD COTS sensors is better than that of CMOS COTS sensors. Both mean pixel value and cumulative pixel value may be used to obtain the photon dose rate. The sensor technology structure difference leads to the different shapes of events. The Compton scattering of 60Co $\gamma $ photons in silicon caused the recorded patterns to show not only dots but also small streaks or traces. The peak value provides the photon energy, while the peak shape and radius can be used to classify the particle. CMOS COTS sensors are suitable for the particle classification, while CCD COTS sensors are better for energy resolution.

Phenological metrics-based crop classification using HJ-1 CCD images and Landsat 8 imagery

ABSTRACTCrop type data are an important piece of information for many applications in agriculture. Extracting crop type using remote sensing is not easy because multiple crops are usually planted into small parcels with limited availability of satellite images due to weather conditions. In this research, we aim at producing crop maps for areas with abundant rainfall and small-sized parcels by making full use of Landsat 8 and HJ-1 charge-coupled device (CCD) data. We masked out non-vegetation areas by using Landsat 8 images and then extracted a crop map from a long-term time-series of HJ-1 CCD satellite images acquired at 30-m spatial resolution and two-day temporal resolution. To increase accuracy, four key phenological metrics of crops were extracted from time-series Normalized Difference Vegetation Index curves plotted from the HJ-1 CCD images. These phenological metrics were used to further identify each of the crop types with less, but easier to access, ancillary field survey data. We used crop area data from the Jingzhou statistical yearbook and 5.8-m spatial resolution ZY-3 satellite images to perform an accuracy assessment. The results show that our classification accuracy was 92% when compared with the highly accurate but limited ZY-3 images and matched up to 80% to the statistical crop areas.

Remote estimation of cyanobacterial blooms using the risky grade index (RGI) and coverage area index (CAI): a case study in the Three Gorges Reservoir, China.

Harmful cyanobacterial blooms are exemplified as a major environmental concern due to producing toxin, and have generated a serious threat to public health. Knowledge on the spatial-temporal distribution of cyanobacterial blooms is therefore crucial for public health organizations and environmental agencies. In this study, field data and charge coupled device (CCD) image were collected in Lakes Gaoyang and Hanfeng of the Three Gorges Reservoir (TGR), China. We conducted the risky grade index (RGI) and coverage area index to develop a feasible estimation framework of cyanobacterial blooms. First, the close relationships between CCD reflectance spectral indices and water quality parameters were constructed based on water optical classification. Then, a regional algorithm for the RGI classification was established by density peaks. Finally, our proposed algorithm was applied to investigate dynamics of cyanobacterial blooms in the two lakes from 6-year series of CCD images. Encouraging results demonstrated that satellite remote sensing in conjunction with field observation can aid in the estimation of cyanobacterial blooms in the TGR.

Noise Model of a Multispectral TDI CCD Imaging System and Its Parameter Estimation of Piecewise Weighted Least Square Fitting

The time-delayed integration (TDI) charge-coupled device (CCD) imaging technology is widely used in remote sensing field and accurate estimation of noise level is essential to assure good performance of denoising. Therefore, in order to achieve images with high signal-to-noise ratio by the TDI CCD sensor, the noise model of the imaging system is investigated. First, the design of the imaging circuit system is presented, and the main noises of the system are analyzed, such as the TDI CCD sensor, amplifiers, and so on. Then a theoretical noise model of the imaging system is established as a priori information. An improved least square fitting method of parameter estimation is proposed. To validate the theoretical model and the proposed method, extensive tests are carried out to obtain multiple uniform images on a developed TDI CCD imaging system. The experiment results confirm that a precise noise model can be achieved by this method and it verifies the theoretical model, meanwhile. It can be used for noise removal and aided design of imaging systems to acquire high-quality images. It is meaningful for remote sensing to obtain more targets of interest.