Separation of leaves and woody materials is crucial for estimation of biophysical attributes of trees such as leaf area index and above-ground biomass. Segmentation based on images from traditional cameras is difficult in low-light level conditions like high canopy density areas and understory vegetation in rain forests. Point clouds from terrestrial laser scanning (TLS) LIDAR are also used for canopy quantitative analysis, but it suffers from low spatial-resolution for leafwood separation. To solve the problems mentioned above, we present a method of wood-leaf separation method based on a dual-wavelength active range-gated imaging system to separate leaves, woody elements, and background. In our method, two overlapped near infrared gated images at the wavelength of 808nm are obtained with background filtered by gated viewing, and a green-channel image is grasped at the illumination of 530nm LED. Then through data preprocessing, these images are input into our separation algorithm. Our separation method uses a peak-search formula to find the target peak in the histogram of an image, and the threshold is the local minimum at the right of the target peak. After segmentation by thresholding, a woody area mask is obtained. Combined with the point clouds reconstructed from gated images, separation on the point clouds is available. We have collected images of vegetation and performed manual separation to test our method. The results show that our method is capable to make accurate classification of leaves, woody elements and background.
Human physiological parameters such as heart rate (HR) and heart rate variability (HRV) hold significant importance in health analysis and disease diagnosis. Traditional measurement methods heavily depend on contact sensors, which are inconvenient and uncomfortable for subjects. In contrast, video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact physiological measurement. However, its utility is compromised by susceptibility to motion artifacts and lighting. In response to the challenges posed by motion artifacts and lighting, we propose a robust rPPG framework. This paper assesses the noise robustness of diverse methods employed in rPPG-based physiological measurement, including face detection and tracking, region of interest (ROI) selection, rPPG signal extraction and heart rate calculation. The experimental results demonstrate the efficacy of the proposed framework in enhancing pre-processing outcomes and facilitating accurate heart rate measurements, even during dynamic motion tasks.
Underwater in-situ darkfield microscopy imaging can grasp excellent resolution and high contrast images for observing transparent and living plankton. However, its limited field of view and shallow depth of field leads to a large amount of redundant data during image acquisition. Manual extraction of regions of interest (ROIs) imposes significant labor and time costs. Therefore, we develop an automatic ROI extraction method to obtain high-quality in-focus individual plankton images from raw images. A multiscale underwater in-situ microscopy system (MUIMS)based on darkfield imaging has been established. The system allows for the monitoring of plankton in the size range from 10μm to 1cm. A series of preprocessing steps are performed on the raw darkfield images to make edge detection and segmentation of plankton regions. This can realize rapid extraction of ROIs from the raw images. A dataset is constructed from these ROIs, and each image is labeled to indicate whether it is a high-quality image. By using a transfer learning strategy, we improve a pre-trained ResNet-18 model and train it to accurately classify high-quality ROIs. The experimental results show that this method can rapidly extract useful information from raw images, achieving an accuracy of over 90% in judging the quality of ROIs. This research is beneficial for building a dataset of high-quality plankton, which provides a crucial data foundation for ecological research and marine biodiversity conservation.
An underwater microbubbles detection and identification method based on dark field imaging is presented, focusing on measurement of the characteristics of microbubbles with high-resolution image capture. The target microbubbles in sampling volume of interest are illuminated by a laser sheet, which is matched with the depth of field. Images are captured in-focus under an observation angle of 90 deg to implement dark field detection, which suppresses the influence of interferential light, such as backlighting, scattering light, and blur caused by defocus. In this configuration, we propose to measure bubble size based on the distance of peak values of two glare points formed by the diffraction and reflection lights. The modified Resnet18 is employed to recognize the bubble images, and the number of bubbles with different diameters in bubble images is counted by template matching. Experimental results show that this dark field configuration allows high resolution imaging and evaluation of the diameter scale of the microbubbles. The precision of bubble recognition and quantification of bubbles within a certain range achieves more than 90%.
KEYWORDS: Education and training, Depth maps, 3D image processing, Data modeling, LIDAR, Stereoscopy, Optical engineering, Visual process modeling, Reflection, Convolution
In recent years, vision-guided three-dimensional (3D) range-gated imaging has broken through the hardware limitations of traditional methods and brought new ideas to the field of 3D range-gated imaging. However, the existing approaches do not consider the uncertainty caused by incomplete training data, which make accuracy of the existing methods still possible for further improvement. In our work, we extend the well-known Gated2Depth framework using epistemic uncertainty by introducing Bayesian neural networks to provide uncertainty that does not exist in the input data due to incomplete training data. Finally, in the proof experiments, mean absolute error achieved 8.7% improvement on the night data and 9% improvement on the daytime data. The improvement of 3D range-gated imaging accuracy reduced the holes and blurred problems in the depth map and obtained sharper target edges.
It needs a triggered time to open or close optical gate of the ICCD. The duration time is defined as irising effect time. Although it only lasts a few nanoseconds and often be ignored by users, it can still interfere with the results in some applications such as fluorescence lifetime imaging and gated imaging. This paper proposes a fitting algorithm to correct the irising effect of the image intensifier. This method obtains fitting matrices of different gates through a series delay images of ICCD. Then through these fitting matrices, the imaging pictures are effectively corrected. The advantages of this method are low cost, high efficiency, and simplicity. The verification experiment of this paper is to write letters with a highlighter. The correction algorithm can clearly restore time-resolve image, and significantly improve the contrast of the image.
Underwater three-dimensional gated range-intensity correlation imaging (3D GRICI) can obtain two-dimensional images with large target-to-background contrast by suppressing backscatter and background noise outside volume of interest (VOI), and simultaneously reconstruct 3D images by the range-intensity correlation algorithm. However, it is still affected by the sub-backscatter noise from VOI in turbid water, resulting in short 3D detection distance and low contrast images. Therefore, in this paper the optical polarization is used for 3D GRICI. Due to the polarization-preserving property of water backscattering, the sub-backscatter noise can be removed from gate images by polarization. Experimental results show that when the water attenuation coefficient is less than or equal to the critical attenuation coefficient of c0, the polarization has no effect on improving detection distance and imaging quality of 3D GRICI; when the water attenuation coefficient is greater than c0, the polarization is helpful for improving performance of 3D GRICI. This research is conducive to optimize the applications of 3D GRICI in turbid water.
With the increasing demand for navigation, obstacle avoidance and exploration, optical cameras are increasingly installed on unmanned underwater vehicles(UUVs). In order to meet the hydrodynamic performance requirements of UUVs, optical camera needs to be equipped inside optical fairing. However, traditional optical fairing can make optical cameras defocus and distortion, due to the difference in refractive index inside and outside the optical fairing. One of the common solutions is to replace the fairing with optical flat panel, but it will increase water resistance of UUV and affect the hydrodynamic performance. Another solution is to choose an optical camera that matches the additional focal length brought by the curvature of optical fairing, so that the optical fairing becomes a part of the camera lens. But the position of optical camera and optical fairing must be set strictly and precisely. Therefore, it is impossible to flexibly change camera, lens, optical fairing, and their positions. In this paper, a novel underwater low-resistance optical fairing is proposed. The shape of optical fairing is designed streamlined to reduce water resistance, and the water-filled structure eliminates the defocus and distortion effects caused by refractive index difference. Numerical simulations are performed to analyze the aberration and distortion caused by optical fairing. Comparison experiments of the proposed optical fairing and traditional optical fairing are performed. It is shown that the proposed fairing is simple in structure and flexible in implementation, which can enable clear imaging of optical cameras, and can be easily installed to achieve better hydrodynamic performance of UUVs.
There are a large number of bubbles in ocean, such as H2S, CH4 and CO2 in hydrothermal and cold springs. Bubbles in
seawater are moving targets with small scale and high transparency, and it is difficult to obtain their clear optical images.
In order to better image tiny bubbles, it is necessary to explore the optical characteristics of bubbles under different angles
of incident light. By building a multi-angle optical characteristic analysis device for underwater bubbles, this paper collects
bubble images at different incident angles, and analyzes the image characteristics of tiny bubbles. The typical bubble
patterns are "hamburger" and "doughnut". In experiment, the bubble groups at different angles were collected and analyzed,
and an orthogonal narrow slice imaging scheme was proposed. The optical slice imaging can obtain clear optical images
of bubbles, which is conducive to quantitative analysis of bubble identification and counting in the later stage.
Underwater high-resolution optical imaging is widely used in marine resource development, ecological monitoring, underwater archaeology, underwater search and rescue, and marine scientific research. However, small field of view (FOV) in optical imaging is ineffective for large scene mapping. Underwater image stitching aims to generate a highresolution panoramic image containing more information from a series of small-FOV and high-resolution images. This paper proposes an underwater optical image stitching method, including image alignment algorithm, optimal seam algorithm, Hue-Saturation-Value correction algorithm based on histogram matching, and multi-resolution fusion algorithm. The experimental results show that the proposed algorithms are effective for targets in different environments, and the panorama can be produced without artifacts or visible seams.
Underwater range gated imaging (RGI) technique has been widely studied since it can well suppress scattering noise from water. The range intensity profile (RIP) plays a vital role in the image quality and range accuracy of underwater 2D and 3D RGI. The existing theoretical analysis for underwater RIPs mainly considers the attenuation effect of water on light propagation. However, it does not take into account the water scattering effect, and thus cannot fully reveal the characteristics of RIPs in underwater RGI. This paper has proposed a RIP analysis method for underwater RGI based on Monte Carlo method. The simulation results show that the water scattering significantly affects the properties of RIP, making it broadening and smoothing. The proposed method and conclusion will contribute to the design of underwater RGI systems, as well as optimizing their operating parameters.
Gated range-intensity correlation 3D imaging is a fast high-resolution 3D imaging technology based on range-gated imaging, and has great potential in underwater imaging, marine life detection and topographic mapping. Pixel gray information between different frame-type 2D images is used to obtain 3D image and distance information. However, for moving platforms (such as underwater vehicles), and moving targets (such as zooplankton, fish, etc.), relative motion will cause two frames of images to be misaligned, eventually leading to failure of 3D inversion. To solve the problem, the inter-frame feature matching for underwater 3D gated range-intensity correlation imaging method is proposed. Feature pairs are matched by the bi-directional feature matching, and mean value of the feature-pair coordinate differences is optimized, the method can solve feature point-to-coordinate deviation caused by water body noise, and improve the robustness of feature point matching. Experimental verification on pools and lakes shows that the proposed method is effective and can realize three-dimensional imaging of relative moving targets.
High-resolution 3D optical imaging is important for unmanned underwater vehicles (UUVs) in the applications of target detection and recognition, underwater engineering, automatic navigation, scientific research, and natural resources exploration. Compared with stereo camera and 3D laser scanning imaging, 3D range-gated imaging (3D RGI) has longer detection range and higher spatial resolution at the same time. This paper presents a survey on 3D range-gated imaging methods for underwater detection. Up to now, there are two main methods developed, including time slicing method and gated range intensity correlation method. The literature about 3D RGI has been reviewed in different detection applications for UUV. We also introduce our works in 3D gated range-intensity correlation imaging for fishing net detection and marine life in-situ detection. This paper is beneficial for the 3D RGI technique in underwater detection applications for UUV.
Fluorescence lifetime imaging (FLI) plays an important role in detection of different fluorescence substances. However, when background light is strong and image noise is high, FLI is hard to discriminate substances with approximate fluorescence lifetime. An enhanced time-resolved fluorescence imaging method is proposed. In the method, a dual-gated intensity-correlation enhancement algorithm is developed. Compared with traditional rapid fluorescence lifetime determination imaging method, the method focuses on improve image contrast and can effectively remove background noise. It utilizes two fluorescence intensity images at different delay times, and adaptively chooses the filter threshold and the up threshold to remove noise and enhance contrast. The thresholds are determined by the distribution of image variance. In proof experiments, three brands of highlighters with the same color have close fluorescence lifetime, and the proposed method shows their fine fluorescence difference. The simulation and experimental results prove that the method can improve the ability of time-resolved fluorescence imaging.
Aiming at the practical application requirements of small dark target recognition for underwater unmanned aerial vehicles, a underwater laser gating imaging target recognition network based on convolutional neural network is designed to classify and identify underwater multiple targets. The integrated tool HLS transplants the network into the FPGA for circuit implementation. Firstly, the algorithm is designed to verify the realization of the convolutional neural network. Then the underwater target recognition experiment is carried out on the implemented convolutional neural network circuit. The network identification accuracy rate is 94% for the three types of underwater target used in the experiment, which verifies the feasibility of convolutional neural network implementation in FPGA.
KEYWORDS: 3D image processing, 3D acquisition, Target detection, Near infrared, Night vision, Stereoscopy, Pulsed laser operation, Gated imaging, Imaging systems, Night vision systems
Traditional NIR laser night vision systems can only obtain 2D images without target range information, and are also easily affected by fog, rain, snow and foreground/background. To solve the problems above, 3D laser night vision based on range-gated imaging has been developed. This paper reviews 3D range-gated imaging advances and focuses on 3D rangeintensity correlation imaging (GRICI) due to its better real time performance and higher spatial resolution. In GRICI systems, the typical illuminator is eye-invisible pulsed semiconductor laser, and the image sensor chooses gated ICCD or ICMOS with mega pixels and ns-scaled gate time. To realize 3D night vision, two overlapped gate images with trapezoidal or triangular range-intensity profiles are grasped by synchronizing the puled laser and the gated sensor. The collapsed range is reconstructed by the range-intensity correlation algorithm, and furthermore 2D and 3D images can both be obtained at the same frame rate. We have established 3D NIR night vision systems based on triangular GRICI, and the experimental results demonstrate that 3D images realize target extraction from background and through windows or smoke. The range resolution minimum is about less than 0.2m at the range of 1km in our GRICI-NV3000, and the range maximum of 3D imaging is about 5km in our GRICI-NV6000.
The underwater optical vision guidance technique is important for AUV short-range docking. Most of the docking lights are blue or green LED lights. However, LED lights have large divergence angle and cannot meet long range optical guidance. In this paper, we designed a blue laser diode docking light named as Beijixing with adjustable divergence angle and carried out the experiment. The divergence angle variation model of the docking light propagating in water is established according to the optical properties of water and the beam-spread function. The experimental results show that at a distance of 18m, when the divergence angle is 0.06° with strong directivity, the images captured by Nano SeaCam appear saturated, and the spot images captured by StarfishCam are light columns, which are difficulty for spot centroid extraction. When the angle is 10°, the light spots captured by Nano-SeaCam overlap, but StarfishCam can distinguish the spots. The research is beneficial for the design of docking lights for underwater optical vision guidance in AUV docking.
Camera traps are commonly used in wildlife monitoring. Traditionally camera traps only capture 2D images of wildlife moving in front of them. However, size information of wildlife is lost, which is vital to determine their ages and genders. To solve this problem, this paper develops a binocular camera trap based on stereo imaging for wildlife detection. The camera trap consists of two cameras, motion sensors, a photosensitive sensor and infrared illumination with the central wavelength of 940nm. Motion sensors output triggers to cameras when animals move past, and then pictures are captured from two different perspectives simultaneously. Meanwhile the photosensitive sensor perceives ambient illumination to control infrared illumination. In this way, the camera trap provides both 2D images of wildlife and their size information obtained by binocular vision. In addition, different from normal binocular cameras placed horizontally, these two cameras are set vertically for the convenience of installation and the expansion of dynamic measure range. As verification, we develop a prototype binocular camera trap to measure a human’s height that is 178cm, and the estimation error approaches 2cm at the distance of 5m.
KEYWORDS: 3D image processing, 3D metrology, Pulsed laser operation, Super resolution, Cameras, 3D acquisition, Imaging systems, Reconstruction algorithms, 3D modeling, Image processing
In this paper, we proposed a method of canopy reconstruction and measurement based on 3D super resolution range-gated imaging. In this method, high resolution 2D intensity images are grasped by active gate imaging, and 3D images of canopy are reconstructed by triangular-range-intensity correlation algorithm at the same time. A range-gated laser imaging system(RGLIS) is established based on 808 nm diode laser and gated intensified charge-coupled device (ICCD) camera with 1392´1040 pixels. The proof experiments have been performed for potted plants located 75m away and trees located 165m away. The experiments show it that can acquire more than 1 million points per frame, and 3D imaging has the spatial resolution about 0.3mm at the distance of 75m and the distance accuracy about 10 cm. This research is beneficial for high speed acquisition of canopy structure and non-destructive canopy measurement.
Moving target detection is important for the application of target tracking and remote surveillance in active range-gated laser imaging. This technique has two operation modes based on the difference of the number of pulses per frame: stroboscopic mode with the accumulation of multiple laser pulses per frame and flash mode with a single shot of laser pulse per frame. In this paper, we have established a range-gated laser imaging system. In the system, two types of lasers with different frequency were chosen for the two modes. Electric fan and horizontal sliding track were selected as the moving targets to compare the moving blurring between two modes. Consequently, the system working in flash mode shows more excellent performance in motion blurring against stroboscopic mode. Furthermore, based on experiments and theoretical analysis, we presented the higher signal-to-noise ratio of image acquired by stroboscopic mode than flash mode in indoor and underwater environment.
A method of ns-scaled time-gated fluorescence lifetime imaging (TFLI) is proposed to distinguish different fluorescent substances in forensic document examination. Compared with Video Spectral Comparator (VSC) which can examine fluorescence intensity images only, TFLI can detect questioned documents like falsification or alteration. TFLI system can enhance weak signal by accumulation method. The two fluorescence intensity images of the interval delay time tg are acquired by ICCD and fitted into fluorescence lifetime image. The lifetimes of fluorescence substances are represented by different colors, which make it easy to detect the fluorescent substances and the sequence of handwritings. It proves that TFLI is a powerful tool for forensic document examination. Furthermore, the advantages of TFLI system are ns-scaled precision preservation and powerful capture capability.
3D range-gated superresolution imaging is a novel 3D reconstruction technique for target detection and recognition with good real-time performance. However, for moving targets or platforms such as airborne, shipborne, remote operated vehicle and autonomous vehicle, 3D reconstruction has a large error or failure. In order to overcome this drawback, we propose a method of stereo matching for 3D range-gated superresolution reconstruction algorithm. In experiment, the target is a doll of Mario with a height of 38cm at the location of 34m, and we obtain two successive frame images of the Mario. To confirm our method is effective, we transform the original images with translation, rotation, scale and perspective, respectively. The experimental result shows that our method has a good result of 3D reconstruction for moving targets or platforms.
An automatic fishing net detection and recognition method for underwater obstacle avoidance is proposed. In the method, optical gated viewing technology is utilized to obtain high-resolution fishing net images and extend detection distance by suppressing water backscattering and background noise. The fishing net recognition is based on the proposed histograms of slope lines (HSLs) descriptors plus a support vector machine classifier. The extraction of HSL descriptors includes five steps of contrast-limited adaptive histogram equalization, the Gaussian low-pass filtering, the Canny detection, the Hough transform, and weighted vote. In the proof experiments, the detection distance of the fishing net reaches 5.7 attenuation length and the recognition accuracy reaches 93.79%.
Laser range-gated imaging has great potentials in remote night surveillance with far detection distance and high resolution, even if under bad weather conditions such as fog, snow and rain. However, the field of view (FOV) is smaller than large objects like buildings, towers and mountains, thus only parts of targets are observed in one single frame, so that it is difficult for targets identification. Apparently, large FOV is beneficial to solve the problem, but the detection range is not available due to low illumination density in a large field of illumination matching with the FOV. Therefore, a large field-of-view range-gated laser imaging is proposed based on image fusion in this paper. Especially an image fusion algorithm has been developed for low contrast images. First of all, an infrared laser range-gated system is established to acquire gate images with small FOV for three different scenarios at night. Then the proposed image fusion algorithm is used for generating panoramas for the three groups of images respectively. Compared with raw images directly obtained by the imaging system, the fused images have a larger FOV with more detail target information. The experimental results demonstrate that the proposed image fusion algorithm is effective to expand the FOV of range-gated imaging.
Underwater range-gated laser imaging (URGLI) still has some problems like un-uniform light, low brightness and contrast. To solve the problems, a variant of adaptive histogram equalization called contrast limited adaptive histogram equalization (CLAHE) is proposed in this paper. In experiment, using the CLAHE and HE to enhance the images, and evaluate the quality of enhanced images by peak signal to noise ratio (PSNR) and contrast. The result shows that the HE gets the images over-enhanced, while the CLAHE has a good enhancement with compressing the over-enhancement and the influence of un-uniform light. The experimental results demonstrate that the CLAHE has a good result of image enhancement for target detection by underwater range-gated laser imaging system.
Underwater 3D range-gated imaging can extend the detection range over underwater stereo cameras, and also has great potentials in real-time high-resolution imaging than 3D laser scanning. In this paper, a triangular-range-intensity profile spatial correlation method is used for underwater 3D range-gated imaging. Different from the traditional trapezoidal method, in our method gate images have triangular range-intensity profiles. Furthermore, inter-frame correlation is used for video-rate 3D imaging. In addition, multi-pulse time delay integration is introduced to shape range-intensify profiles and realize flexible 3D SRGI. Finally, in experiments, 3D images of fish net, seaweed and balls are obtained with mm-scaled spatial and range resolution.
Three-dimensional super-resolution range-gated imaging (3D SRGI) is a new technique for high-resolution 3D sensing. Up to now, 3D SRGI has been developed with two range-intensity correlation algorithms, including trapezoidal algorithm and triangular algorithm. To obtain high depth-to-resolution ratio of 3D imaging, coding method was developed for 3D SRGI based on the trapezoidal algorithm in 2011. In this paper, we propose the range-intensity coding based on the triangular algorithm and the hybrid range-intensity coding based on the triangular and trapezoidal algorithms. The theoretical models to predict the maximum coding bin number are developed for different coding methods. In the models, the maximum coding bin number is 7 for three coding gate images under the triangular algorithm, and the maximum is extended to 16 under the hybrid algorithm. The coding examples of 7 bins and 16 bins mentioned above are also given in this paper. The comparison among the three coding methods is performed by the depth-to-resolution ratio defined as the ratio between the 3D imaging depth and the product of the range resolution and raw gate image number, and the hybrid coding method has the highest depth-to-resolution ratio. Higher depth-to-resolution ratio means better 3D imaging capability of 3D SRGI.
Three-dimensional super-resolution range-gated imaging has been developed for high-resolution 3D remote sensing with two range-intensity correlation algorithms under specific shapes of range-intensity profiles (RIP). However, pulsed lasers have a minimum pulse width which limits range resolution improvement. Here a spatial difference shaping method is proposed to break the resolution limitation. This method establishes a shaping filter, and the pre-reshaping gate images are reshaped by spatial difference and yield new gate images with the laser pulse width equivalently narrowed as half value which improves the range resolution. Furthermore, the boundary blurring caused by non-rectangular laser pulses are also eliminated.
Three-dimensional range-gated imaging is a new 3D sensing technique with higher resolution than 3D flash LIDAR,
and has great potential in realizing high-resolution real-time 3D imaging to satisfy land surface remote sensing
applications. In this paper, three existing approaches of realizing 3D range-gated LIDAR are introduced including their
advantages and disadvantages. Among them, the two methods of gain modulation and range-intensity correlation can
reconstruct a 3D scene from two gate images, which enable 3D flash imaging. We propose a 3D superresolution
range-gated flash LIDAR based on triangular algorithm of range-intensity correlation, and further present a coding
method based on triangular algorithm for high depth-to-resolution ratio. Some prototyping experiments and simulations
are demonstrated.
High-resolution real-time three-dimensional imaging is important in 3D video surveillance, robot vision, and
automatic navigation. In this paper, a three-dimensional superresolution range-gated imaging based on inter-frame
correlation is proposed to realize high-resolution real-time 3D imaging. In this method, a CCD/CMOS with a gated
image intensifier is used as image sensor, and depth information collapsed in 2D images is reconstructed by
spatial-temporal inter-frame correlation with a resolution of about 1000×1000 full-frame pixels within a frame.
Furthermore, under inter-frame correlation a 3D point cloud frame is generated at video rates corresponding to
CCD/CMOS utilized. Finally, some proof simulation experiments are demonstrated.
The range-gated laser imaging technology has become a useful technique in many applications in recent years. In
order to expand the range of imaging detection and improve the measurement range resolution of the imaging system, we
used circular step advance delay sequence for the synchronous control. And we developed a method of using dynamic
phase-shift technique in FPGA to improve the precision of the delay in the time sequence, which can make the precision
of the delay stepper between the two adjacent frames less than global clock period of the FPGA and approach the limit of
FPGA’s operating frequency. That is to say, it can equivalently increase the clock frequency. Then we can effectively
improve measurement range resolution of the imaging system. In this paper, we have studied how dynamic phase-shift
technique can be equivalent to higher clock frequency and performed some experiments. We presented the structure of
dynamic phase-shift technique used to improve the precision of delay in the synchronization control time sequence. And
the simulation and experimental results are showed in this paper. The results demonstrate that using dynamic phase-shift
technique in FPGA can make the precision of the delay between the ICCD’s trigger pulse and the laser’s trigger pulse
reach 1ns, which means the resolution of measurement range can be 0.15m theoretically. The timing control signal with
dynamic phase-shift technique designed in this paper can be widely used in range-gated imaging because of its high
timing control precision and flexible parameter setting.
Echo broadening effect (EBE) is inherent in three-dimensional range-gated imaging (3DRGI). The effect impacts the
range-intensity profile of gate images which is crucial in three approaches of 3DRGI based on depth scanning,
supperresolution depth mapping and gain modulation. In this paper, we give the space-time model of EBE which
illustrates three typical range-intensity profiles under different temporal parameters of laser pulse and gate pulse. A head
zone and a tail zone exist in both sides of the profiles. Our research demonstrates that EBE should be suppressed in depth
scanning and gain modulation methods and utilized in supperresolution depth mapping.
Target acquisition is of great importance for ship borne range-gated night vision system which can achieve target finding,
target tracing and ranging. A digital image processing algorithm is developed for the mentioned night vision equipment
above. Target contour is extracted using Canny edge detection algorithm based on self-adapted Otsu threshold
segmentation. Furthermore, edge thinning, edge connection and morphologic methods are implemented to ameliorate the
acquired contour. Pixels inside the contour are collected utilizing horizontal-vertical traverse. After ship targets from
range-gated equipment being all tested, target contour and inner pixels can both be acquired through this algorithm.
Target tracking is of great importance in imaging system, which can be applied in surveillance, as well as salvage and rescue where 3D spatial coordinates are used to locate the target. Range-gated imaging system is capable of acquiring range information of targets. However, azimuth is also necessary to provide the spatial coordinates to achieve target tracking. This paper presents a target azimuth estimation method for range-gated imaging system, aiming at obtaining essential information for vision-based automatic tracking. Due to the noise and low contrast of range-gated image, median filter and histogram equalization are used. Then the Otsu method is performed to make the segmentation of target and background. After segmentation, morphologic transformation methods will be taken in order to delete false targets. With pixels of target extracted from the image, the centoid will be derived. Next the pinhole camera model is applied to work out the azimuth coordinate. Since the focus length of camera is needed in the formula, an NC (Numerical Control) zoom module is developed. In this module, a sliding potentiometer is connected to the focus motor in camera, which serves as a feedback of the focus. To read the focus length and control the focus motor, an MCU (with AD converter) is used. Once the target azimuth information is obtained, the pan-tilt control unit can track the target bit by bit automatically.
Coastal surveillance is very important because it is useful for search and rescue, illegal immigration, or harbor security and so on. Furthermore, range estimation is critical for precisely detecting the target. Range-gated laser imaging sensor is suitable for high accuracy range especially in night and no moonlight. Generally, before detecting the target, it is necessary to change delay time till the target is captured. There are two operating mode for range-gated imaging sensor, one is passive imaging mode, and the other is gate viewing mode. Firstly, the sensor is passive mode, only capturing scenes by ICCD, once the object appears in the range of monitoring area, we can obtain the course range of the target according to the imaging geometry/projecting transform. Then, the sensor is gate viewing mode, applying micro second laser pulses and sensor gate width, we can get the range of targets by at least two continuous images with trapezoid-shaped range intensity profile. This technique enables super-resolution depth mapping with a reduction of imaging data processing. Based on the first step, we can calculate the rough value and quickly fix delay time which the target is detected. This technique has overcome the depth resolution limitation for 3D active imaging and enables super-resolution depth mapping with a reduction of imaging data processing. By the two steps, we can quickly obtain the distance between the object and sensor.
We present a method of target detection against strong light based on gate viewing. In this method, a nanosecond-scale
gate shutter is used to control the exposure time of CCD and reduce the collection of obtrusive light, and a
nanosecond-scale pulsed laser is used to illuminate targets and increase signal energy. By matching them, the ratio
between signal and obtrusive light will be significantly improved to detect targets against light disturbance. We have
analyzed the method in theory, and performed it in experiment. In addition, a stroboscopic time sequence is used, and the
setting of temporal parameters is also discussed.
This paper presents a novel algorithm to extract signal area of range-gated images under the EBE effect. Besides
the histogram information, this algorithm uses average gray value information to select threshold with iterative
processing. With average gray value information, the edges of signal area can be segmented out accurately. The
algorithm can handle images under the impact of EBE effect, reduce the noise in the images and segment the
objects from the noise area effectively without many morphological operations which keeps the certain figure from
distortion. Experiment result shows that the algorithm is effective to the signal areas extraction of images under
EBE effect, signal areas can be segmented out accurately.
KEYWORDS: Picosecond phenomena, Field programmable gate arrays, 3D image processing, Stereoscopy, Signal generators, Data transmission, Phase shifts, Control systems, Pulsed laser operation, 3D acquisition
3D range-gated imaging with stepping delay is a novel technology developed in recent years. 3D timing control signal
based on delay line and logical AND gate technology is proposed innovatively in order to satisfy the distance precision
of centimeter of 3D imaging in complex background. 3D timing control signal is produced through FPGA nanosecond
timing generation module and picosecond timing adjustment module. Simulation and experiment show that the delay
precision of the timing signal designed in this paper is 150 picoseconds, and the narrowest pulse width is close to the
limitation of TTL signal (1ns level). The timing control signal designed in this paper can be widely used in 3D
range-gated imaging because of its high timing control precision, compact construction and flexible parameter setting.
Keywords: range-gated, picosecond, timing control, FPGA, delay line
We propose a surveillance photonic fence for night remote intrusion detection, especially in bad environmental
conditions. The photonic fence is established by the synchronization of a pulsed infrared laser and a gated imaging sensor.
Since the wavelength of the laser is invisible, the photonic fence is also invisible. Only when targets pass the fence, their
image information can be collected. Objects and backgrounds out of the fence are all filtered directly which decreases the
complexity of image processing about target extraction. For the fence, its location can be easily adjusted by the delay
time between the laser pulse and the gate pulse, and its thickness can be set by changing the gate time and the laser pulse
width. Furthermore, target space information can also be estimated in terms of the range information of the photonic
fence.
We present a flash trajectory imaging technique which can directly obtain target trajectory and realize non-contact
measurement of motion parameters by range-gated imaging and time delay integration. Range-gated imaging gives the
range of targets and realizes silhouette detection which can directly extract targets from complex background and
decrease the complexity of moving target image processing. Time delay integration increases information of one single
frame of image so that one can directly gain the moving trajectory. In this paper, we have studied the algorithm about
flash trajectory imaging and performed initial experiments which successfully obtained the trajectory of a falling
badminton. Our research demonstrates that flash trajectory imaging is an effective approach to imaging target trajectory
and can give motion parameters of moving targets.
We have presented the Echo Broadening Effect of range-gated active imaging. It can respectively generate a head
signal part and a tail signal part both sides of the echo signal profile. Our research demonstrates that the head signal
and the tail signal impact the depth of view, detection range and imaging quality, especially the head signal. In order
to solve the problems, we establish a model of the echo broadening effect, and analyze the signal energy
characteristics and atmospheric backscatter. We have given the depth of view under the effect, verified it in
experiment, and found that the reasonable choosing of the illuminator laser pulse time and the camera gate time can
mange the effect to optimize range-gated imaging systems.
We design a new double-layer grating template, which has the advantages of period uniformity, period number adjustability and continuous period regulation. Under the new template, we research the relationship between the spectrum and the grating templates: the resonant wavelength is mainly determined by the grating period; the intensity of transmission peak loss lies in the external pressures; the bandwidth of transmission spectrum can be controlled by the period number. Therefore, various applications can be realized by optimizing the transmission spectrum by reasonably selecting the matched parameters.
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