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The interaction between a moving submarine and seawater generates characteristic wakes on the sea surface, enabling indirect detection of undersea objects via airborne remote sensing. Here, we demonstrate the feasibility of using visible-light polarization imaging to observe submarine wakes. The key links in the imagine chain are considered separately. These include the polarization patterns of skylight, the elevations and slopes of submarine wakes and sea waves, and the changes in the sea surface polarized bidirectional reflectance characteristics due to modulation of gravity–capillary waves by the wake’s velocity field. A complete model of the airborne optical polarization imaging process is constructed and images are simulated via ray tracing. All theories proposed are verified by a series of terrestrial observation experiments. The results show that both the sea surface roughness modulation by the wake’s velocity field and the sea surface slope formed by wake elevation play significant roles in the imaging process. The wake features in the Stokes vector linear polarization component (Q, U) images are effectively enhanced, and the environmental adverse effect on these images is smaller than that on the intensity images. The degree of linear polarization (DoLP) and angle of polarization (AoP) images exhibit acceptable contrast under certain zenith and azimuth angles. Thus, our analysis confirms that airborne optical polarization imaging has considerable potential for observing wakes and other small- and medium-scale ocean dynamic processes.
Fuduo Xue; Weiqi Jin; Su Qiu; Jie Yang. Airborne optical polarization imaging for observation of submarine Kelvin wakes on the sea surface: Imaging chain and simulation. ISPRS Journal of Photogrammetry and Remote Sensing 2021, 178, 136 -154.
AMA StyleFuduo Xue, Weiqi Jin, Su Qiu, Jie Yang. Airborne optical polarization imaging for observation of submarine Kelvin wakes on the sea surface: Imaging chain and simulation. ISPRS Journal of Photogrammetry and Remote Sensing. 2021; 178 ():136-154.
Chicago/Turabian StyleFuduo Xue; Weiqi Jin; Su Qiu; Jie Yang. 2021. "Airborne optical polarization imaging for observation of submarine Kelvin wakes on the sea surface: Imaging chain and simulation." ISPRS Journal of Photogrammetry and Remote Sensing 178, no. : 136-154.
Image intensifiers are used internationally as advanced military night-vision devices. They have better imaging performance in low-light-level conditions than CMOS/CCD. The intensified CMOS (ICMOS) was developed to satisfy the digital demand of image intensifiers. In order to make the ICMOS capable of color imaging in low-light-level conditions, a liquid-crystal tunable filter based color imaging ICMOS was developed. Due to the time-division color imaging scheme, motion artifacts may be introduced when a moving target is in the scene. To solve this problem, a deformable kernel prediction neural network (DKPNN) is proposed for joint denoising and motion artifact removal, and a data generation method which generates images with color-channel motion artifacts is also proposed to train the DKPNN. The results show that, compared with other denoising methods, the proposed DKPNN performed better both on generated noisy data and on real noisy data. Therefore, the proposed DKPNN is more suitable for color ICMOS denoising and motion artifact removal. A new exploration was made for low-light-level color imaging schemes.
Zhenghao Han; Li Li; Weiqi Jin; Xia Wang; Gangcheng Jiao; Xuan Liu; Hailin Wang. Denoising and Motion Artifact Removal Using Deformable Kernel Prediction Neural Network for Color-Intensified CMOS. Sensors 2021, 21, 3891 .
AMA StyleZhenghao Han, Li Li, Weiqi Jin, Xia Wang, Gangcheng Jiao, Xuan Liu, Hailin Wang. Denoising and Motion Artifact Removal Using Deformable Kernel Prediction Neural Network for Color-Intensified CMOS. Sensors. 2021; 21 (11):3891.
Chicago/Turabian StyleZhenghao Han; Li Li; Weiqi Jin; Xia Wang; Gangcheng Jiao; Xuan Liu; Hailin Wang. 2021. "Denoising and Motion Artifact Removal Using Deformable Kernel Prediction Neural Network for Color-Intensified CMOS." Sensors 21, no. 11: 3891.
RGBN cameras that can capture visible light and near-infrared (NIR) light simultaneously produce better color image quality in low-light-level conditions. However, these RGBN cameras introduce additional color bias caused by the mixing of visible information and NIR information. The color correction matrix model widely used in current commercial color digital cameras cannot handle the complicated mapping function between biased color and ground truth color. Convolutional neural networks (CNNs) are good at fitting such complicated relationships, but they require a large quantity of training image pairs of different scenes. In order to achieve satisfactory training results, large amounts of data must be captured manually, even when data augmentation techniques are applied, requiring significant time and effort. Hence, a data generation method for training pairs that are consistent with target RGBN camera parameters, based on an open access RGB-NIR dataset, is proposed. The proposed method is verified by training an RGBN camera color restoration CNN model with generated data. The results show that the CNN model trained with the generated data can achieve satisfactory RGBN color restoration performance with different RGBN sensors.
Zhenghao Han; Li Li; Weiqi Jin; Xia Wang; Gangcheng Jiao; Hailin Wang. Convolutional Neural Network Training for RGBN Camera Color Restoration Using Generated Image Pairs. IEEE Photonics Journal 2020, 12, 1 -15.
AMA StyleZhenghao Han, Li Li, Weiqi Jin, Xia Wang, Gangcheng Jiao, Hailin Wang. Convolutional Neural Network Training for RGBN Camera Color Restoration Using Generated Image Pairs. IEEE Photonics Journal. 2020; 12 (5):1-15.
Chicago/Turabian StyleZhenghao Han; Li Li; Weiqi Jin; Xia Wang; Gangcheng Jiao; Hailin Wang. 2020. "Convolutional Neural Network Training for RGBN Camera Color Restoration Using Generated Image Pairs." IEEE Photonics Journal 12, no. 5: 1-15.
Zhenghao Han; Weiqi Jin; Li Li; Xia Wang; Xiaofeng Bai; Hailin Wang. Nonlinear Regression Color Correction Method for RGBN Cameras. IEEE Access 2020, 8, 25914 -25926.
AMA StyleZhenghao Han, Weiqi Jin, Li Li, Xia Wang, Xiaofeng Bai, Hailin Wang. Nonlinear Regression Color Correction Method for RGBN Cameras. IEEE Access. 2020; 8 ():25914-25926.
Chicago/Turabian StyleZhenghao Han; Weiqi Jin; Li Li; Xia Wang; Xiaofeng Bai; Hailin Wang. 2020. "Nonlinear Regression Color Correction Method for RGBN Cameras." IEEE Access 8, no. : 25914-25926.
The interaction between a moving submerged body and a homogeneous/stratified fluid generates a Bernoulli hump, a Kelvin wake, and an internal wake on the water surface. The height distribution of wakes is directly related to the location and motion state of the submerged body. Thus, it is possible to retrieve kinematics information of a submarine from the images of wakes obtained by photoelectric detection equipment. In order to extract the submarine’s location and velocity information effectively from the wake photoelectric images, we investigate the relationship between the motion state of moving submerged bodies and wakes in this paper. Bernoulli hump, Kelvin wake, and internal wake models are established based on potential flow theory and thin-ship approximation. We analyzed the wave crestline pattern and the energy characteristics of Kelvin wake components (divergent and transverse waves) and internal wakes at different velocities and diving depths. Finally, we propose a method for estimating the velocity of a submarine based on the wake wavelength and the diving depth inversion method based on the Fourier power spectrum of the Kelvin wake. The results obtained prove the feasibility of using photoelectric equipment to obtain wake images for use in analyzing the kinematics state of submarines, which are of guiding significance for detection and information processing in real-scale submarines.
Fuduo Xue; Weiqi Jin; Su Qiu; Jie Yang. Wake Features of Moving Submerged Bodies and Motion State Inversion of Submarines. IEEE Access 2020, 8, 12713 -12724.
AMA StyleFuduo Xue, Weiqi Jin, Su Qiu, Jie Yang. Wake Features of Moving Submerged Bodies and Motion State Inversion of Submarines. IEEE Access. 2020; 8 (99):12713-12724.
Chicago/Turabian StyleFuduo Xue; Weiqi Jin; Su Qiu; Jie Yang. 2020. "Wake Features of Moving Submerged Bodies and Motion State Inversion of Submarines." IEEE Access 8, no. 99: 12713-12724.
In high dynamic range (HDR) scenes containing strong local radiation, infrared images acquired with a single integration time cannot preserve the details of both bright and dark regions due to the limited dynamic range of the detector. Fusing multiple infrared images captured with variable integration times is an effective method for extending the dynamic range of infrared imaging systems. Fusion algorithms are critical to the visual quality of the results of this technique. In this paper, we propose a fusion algorithm based on grayscale-gradient estimation for infrared images with multiple integration times. In our algorithm, an objective grayscale image and an objective gradient map are first estimated, then they are substituted into the optimization framework for image fusion, and finally, a fused image with appropriate grayscale and gradient distribution is obtained by solving a minimization problem. Experiments show that the proposed algorithm works well under both normal and HDR infrared scenarios. Compared with existing typical multiple exposure fusion algorithms, the proposed algorithm produces better results in terms of noise suppression, visual information fidelity and perceptual quality. Therefore, the proposed algorithm has potential in thermal vision applications involving high dynamic range scenarios and has a high reference value for research in HDR thermal imaging technology.
Shuo Li; Weiqi Jin; Li Li; Mingcong Liu; Jianguo Yang. Fusion algorithm based on grayscale-gradient estimation for infrared images with multiple integration times. Infrared Physics & Technology 2019, 105, 103179 .
AMA StyleShuo Li, Weiqi Jin, Li Li, Mingcong Liu, Jianguo Yang. Fusion algorithm based on grayscale-gradient estimation for infrared images with multiple integration times. Infrared Physics & Technology. 2019; 105 ():103179.
Chicago/Turabian StyleShuo Li; Weiqi Jin; Li Li; Mingcong Liu; Jianguo Yang. 2019. "Fusion algorithm based on grayscale-gradient estimation for infrared images with multiple integration times." Infrared Physics & Technology 105, no. : 103179.
The dynamic range of night vision scenes is typically very large. Owing to the limited dynamic range of the traditional low-light-level imaging technology, the captured images are always partially overexposed or underexposed. Multi-exposure fusion is the most effective method for overcoming the dynamic range limitations of sensors. Recently, deep learning has achieved tremendous progress in many fields. However, only a few breakthroughs have been reported on high-dynamic image fusion with the deep learning method. Additionally, many problems have been reported in conjunctions with commonly used deep-learning methods. In this study, a high-dynamic image fusion algorithm is proposed based on the decomposition convolution neural network and weighted sparse representation. Based on image decomposition, the problem of the acquisition in training samples in network training can be solved. Therefore, the classification accuracy of the network can be improved. Additionally, the decomposition structure reduces the workload of each layer and improves the efficiency and quality of the image fusion outcome.
Guo Chen; Li Li; Wei Qi Jin; Shuo Li. High-Dynamic Range, Night Vision, Image-Fusion Algorithm Based on a Decomposition Convolution Neural Network. IEEE Access 2019, 7, 169762 -169772.
AMA StyleGuo Chen, Li Li, Wei Qi Jin, Shuo Li. High-Dynamic Range, Night Vision, Image-Fusion Algorithm Based on a Decomposition Convolution Neural Network. IEEE Access. 2019; 7 (99):169762-169772.
Chicago/Turabian StyleGuo Chen; Li Li; Wei Qi Jin; Shuo Li. 2019. "High-Dynamic Range, Night Vision, Image-Fusion Algorithm Based on a Decomposition Convolution Neural Network." IEEE Access 7, no. 99: 169762-169772.
Generally, the dynamic range of night vision scenes is large. Owing to the limited dynamic range of traditional low light imaging technology, the captured images are always partially overexposed or underexposed. Multi-exposure fusion is the most effective method of overcoming the dynamic range limitation of sensor, and multi-frame low dynamic range (LDR) image fusion is a key consideration. However, existing fusion methods have problems such as image detail blurring and image aliasing. This paper proposes an image multi-scale decomposition method based on gradient domain guided filter (GDGF), which can better extract image details. The fusion algorithm adopts different fusion strategies for different scales. The low-frequency layer of the image uses a new weighted sparse representation (wSR) method, which can eliminate the image boundary problems and more adequately retain the image edges.
Guo Chen; Li Li; Weiqi Jin; Su Qiu; Hui Guo. Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera. IEEE Photonics Journal 2019, 11, 1 -15.
AMA StyleGuo Chen, Li Li, Weiqi Jin, Su Qiu, Hui Guo. Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera. IEEE Photonics Journal. 2019; 11 (5):1-15.
Chicago/Turabian StyleGuo Chen; Li Li; Weiqi Jin; Su Qiu; Hui Guo. 2019. "Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera." IEEE Photonics Journal 11, no. 5: 1-15.
An image Mosaic algorithm utilizing image overlap rate prior is proposed for bionic compound eye imaging system based on micro-surface fiber faceplate in this paper. Firstly, the two images to be spliced together are both divided into overlapping regions and non-overlapping regions using the prior of relative position and overlap rate of the sub-eye images. Then, Feature points in overlapping regions are extracted using Speeded Up Robust Features (SURF) detector and described by Binary Robust Independent Elementary Features (BRIEF) descriptor. The initial matching of the feature points is made with the hamming distance matching. Random Sample Consensus (RANSAC) and angular consistency of the pairing feature points are used to further purify the feature point pairs. Finally, the weighted mean method is used on the images after registration to get the blended image. The sub-eye images are spliced in each layer and then the spliced images of each layer are stitched together successively to get the final panoramic image. Experimental results showed that the splicing speed of the proposed algorithm is 2 to 3 times higher than that of Scale Invariant Feature Transform (SIFT) algorithm. Compared with SURF algorithm, the splicing speed also increased by about 50%. In addition, more correct matching can be remained, so that the results of image registration and splicing can be more reliable. Thus, the proposed algorithm can promote the images real-time processing of the compound eye imaging system.
Zhuang-Zhuang Zhang; Su Qiu; Wei-Qi Jin; Chao Yang; Jia-An Xue. Image mosaic of bionic compound eye imaging system based on image overlap rate prior. Optical Sensing and Imaging Technologies and Applications 2018, 10846, 108462C .
AMA StyleZhuang-Zhuang Zhang, Su Qiu, Wei-Qi Jin, Chao Yang, Jia-An Xue. Image mosaic of bionic compound eye imaging system based on image overlap rate prior. Optical Sensing and Imaging Technologies and Applications. 2018; 10846 ():108462C.
Chicago/Turabian StyleZhuang-Zhuang Zhang; Su Qiu; Wei-Qi Jin; Chao Yang; Jia-An Xue. 2018. "Image mosaic of bionic compound eye imaging system based on image overlap rate prior." Optical Sensing and Imaging Technologies and Applications 10846, no. : 108462C.
The small video camera of the video life detector, which can go into the narrow space that the rescuers can hardly reach, is used to get color video of the trapped people in the ruins after the disasters such as earthquake. Due to the covering of rubble and dust, it is difficult to detect the position of the trapped persons effectively and judge their physical condition from the video, which affects the search efficiency during the golden time of 72 hours for rescue. In this paper, a small dual-band (LWIR/VIS) video camera with common optical path is designed. The dual-band video camera contains a micro color video camera for details of the scene and a miniaturized thermal imaging component which has a micro uncooled infrared focal plane array (IRFPA) as the detector for capturing the location and vitality of trapped people. The field of view (FOV) of the color video camera, is partly matched with the FOV of the IRFPA component through a hot mirror as the visible and infrared optical splitter. In other words, the FOV of the dual-band imaging system is designed in common path. Then a real-time fusion algorithm of dual-band video is implemented on a DSP hardware image processing platform. As a result, the people and other hot targets in the scene are highlighted in the fused video, which can provide a basis for target detection and decision-making in the rescue process.
Xiaojie Zhu; Weiqi Jin; Li Li; Xia Wang; Su Qiu; Yixin Guo. A small dual-band (LWIR/VIS) color video camera with common optical path and its real-time fusion method. Infrared, Millimeter-Wave, and Terahertz Technologies V 2018, 10826, 108260Y .
AMA StyleXiaojie Zhu, Weiqi Jin, Li Li, Xia Wang, Su Qiu, Yixin Guo. A small dual-band (LWIR/VIS) color video camera with common optical path and its real-time fusion method. Infrared, Millimeter-Wave, and Terahertz Technologies V. 2018; 10826 ():108260Y.
Chicago/Turabian StyleXiaojie Zhu; Weiqi Jin; Li Li; Xia Wang; Su Qiu; Yixin Guo. 2018. "A small dual-band (LWIR/VIS) color video camera with common optical path and its real-time fusion method." Infrared, Millimeter-Wave, and Terahertz Technologies V 10826, no. : 108260Y.
Contrast enhancement for infrared images is important in various night vision applications. However, existing local contrast enhancement algorithms often over-enhance smooth regions in outdoor infrared images. To address this limitation, this paper presents a contrast enhancement algorithm based on local gradient-grayscale statistical feature. The proposed algorithm first extracts such features from image sub-blocks, then classifies the sub-blocks as either simple or non-simple based on textural complexity using a model trained by a support vector machine, and subsequently adopts different grayscale mapping strategies to process the two types separately. Experimental results show that the proposed algorithm avoids over-enhancing simple regions while effectively improving the contrast in regions with more details.
Shuo Li; Weiqi Jin; Xia Wang; Li Li; Mingcong Liu. Contrast Enhancement Algorithm for Outdoor Infrared Images Based on Local Gradient-Grayscale Statistical Feature. IEEE Access 2018, 6, 57341 -57352.
AMA StyleShuo Li, Weiqi Jin, Xia Wang, Li Li, Mingcong Liu. Contrast Enhancement Algorithm for Outdoor Infrared Images Based on Local Gradient-Grayscale Statistical Feature. IEEE Access. 2018; 6 ():57341-57352.
Chicago/Turabian StyleShuo Li; Weiqi Jin; Xia Wang; Li Li; Mingcong Liu. 2018. "Contrast Enhancement Algorithm for Outdoor Infrared Images Based on Local Gradient-Grayscale Statistical Feature." IEEE Access 6, no. : 57341-57352.
Polarization imaging technology provides information about not only the irradiance of a target but also the degree of polarization and angle of polarization, which indicate extensive application potential in the field of ocean remote sensing. Natural light can be converted into partially polarized light by the reflection from an interface, and the Fresnel equations can describe the quantitative relationship between the angle of incidence and the degree of polarization of the reflected light. However, the relationship between the angle of polarization and angle of incidence has rarely been studied. In this study, we investigate the polarization state model of reflected light and establish the relationship between the angle of polarization and angle of incidence. This is verified using polarization imaging experiments on a glass plate and calm water surface. The results indicate that the theoretical model agrees well with the experimental results. A method to eliminate the ambiguity of the angle of incidence is proposed based on the model, and its effectiveness and feasibility are verified. It lays the theoretical foundation for imaging detection based on the polarization imaging of transparent media surfaces and sea surface ripples.
Xiaotian Lu; Jie Yang; Weiqi Jin; Li Li; Xia Wang; Su Qiu. Polarization properties of reflected light with natural light incidence and elimination of angle of incidence ambiguity. Applied Optics 2018, 57, 8549 -8556.
AMA StyleXiaotian Lu, Jie Yang, Weiqi Jin, Li Li, Xia Wang, Su Qiu. Polarization properties of reflected light with natural light incidence and elimination of angle of incidence ambiguity. Applied Optics. 2018; 57 (29):8549-8556.
Chicago/Turabian StyleXiaotian Lu; Jie Yang; Weiqi Jin; Li Li; Xia Wang; Su Qiu. 2018. "Polarization properties of reflected light with natural light incidence and elimination of angle of incidence ambiguity." Applied Optics 57, no. 29: 8549-8556.
The multi-exposure fusion method is an effective way to extend the dynamic range of the infrared focal plane array (IRFPA), but the traditional method doesn’t take into account the impact of the integration time on every pixel’s response function, thereby introducing nonuniform noises and affecting the fusion quality. Based on the traditional response model of an infrared detector, this article derives the relationship between the response function and the integration time by introducing new influence factors, and conducts verification experiments with MW and LW thermal cameras. The experimental results are consistent with the proposed model, which shows that, within the linear response range of the detector, the gain parameters of the pixels are independent of the integration time, and the offset parameters are approximately inversely proportional to it when the ambient temperature is determined. Meanwhile, based on the results, an infrared HDR image fusion method under a variable integration time is studied. The resulting images retain more details of the bright and dark areas of the scene, and the nonuniformity can be corrected to some extent at the same time. This proves that the model proposed in this paper is effective for extending the dynamic range of the IRFPA and has theoretical significance and practical value for further HDR thermal imaging research.
Mingcong Liu; Shuo Li; Li Li; Weiqi Jin; Guo Chen. Infrared HDR image fusion based on response model of cooled IRFPA under variable integration time. Infrared Physics & Technology 2018, 94, 191 -199.
AMA StyleMingcong Liu, Shuo Li, Li Li, Weiqi Jin, Guo Chen. Infrared HDR image fusion based on response model of cooled IRFPA under variable integration time. Infrared Physics & Technology. 2018; 94 ():191-199.
Chicago/Turabian StyleMingcong Liu; Shuo Li; Li Li; Weiqi Jin; Guo Chen. 2018. "Infrared HDR image fusion based on response model of cooled IRFPA under variable integration time." Infrared Physics & Technology 94, no. : 191-199.
This publisher’s note amends the author listing in Appl. Opt. 57, 3991 (2018) [CrossRef] .
Xu Zhang; Weiqi Jin; Li Li; Xia Wang; Ji Chen; Yuchao Jia. Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array: publisher’s note. Applied Optics 2018, 57, 5257 -5257.
AMA StyleXu Zhang, Weiqi Jin, Li Li, Xia Wang, Ji Chen, Yuchao Jia. Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array: publisher’s note. Applied Optics. 2018; 57 (19):5257-5257.
Chicago/Turabian StyleXu Zhang; Weiqi Jin; Li Li; Xia Wang; Ji Chen; Yuchao Jia. 2018. "Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array: publisher’s note." Applied Optics 57, no. 19: 5257-5257.
Targeting star-like water surface clutter, a clutter suppression method based on infrared polarization information is proposed. First, the clutter is suppressed from a global perspective using infrared polarization imaging technology, and a basic clutter-suppressed image is obtained. Then, using the Reed–Xiaoli anomaly detection algorithm, the remaining clutter positions in the basic image are determined from the polarization intensity image and basic image. Finally, an image filtering algorithm is utilized to further suppress the remaining clutter in the basic image. In experiments, the proposed method can not only improve the signal-to-clutter ratio as much as 152%, but also preserve the target information and background texture features effectively, indicating clear superiority of our method over existing clutter suppression algorithms. Clutter suppression and target detail preservation can enhance observer understanding of a scene significantly, so this method is applied to the detection and recognition of targets on the water surface.
Jian-An Liang; Xia Wang; Yu-Jie Fang; Jing-Jing Zhou; Si He; Wei-Qi Jin. Water surface-clutter suppression method based on infrared polarization information. Applied Optics 2018, 57, 4649 -4658.
AMA StyleJian-An Liang, Xia Wang, Yu-Jie Fang, Jing-Jing Zhou, Si He, Wei-Qi Jin. Water surface-clutter suppression method based on infrared polarization information. Applied Optics. 2018; 57 (16):4649-4658.
Chicago/Turabian StyleJian-An Liang; Xia Wang; Yu-Jie Fang; Jing-Jing Zhou; Si He; Wei-Qi Jin. 2018. "Water surface-clutter suppression method based on infrared polarization information." Applied Optics 57, no. 16: 4649-4658.
The scanning infrared focal plane array (IRFPA) suffers from stripe-like non-uniformity due to the usage of many detectors, especially when working with a large time scale. Typical calibration systems tend to block the sensor aperture and expose the detectors to an on-board blackbody calibration source. They may also point at deep space. Full aperture calibration sources of this type tend to be large and expensive. To address these problems, a dynamic non-uniformity correction (NUC) method is proposed based on a modulated internal calibration device. By employing the on-board calibration device to generate a dynamic scene and fully integrating the system characteristics of the scanning IRFPA into the scene-based non-uniformity correction (SBNUC) algorithm, on-orbit high dynamic range NUC is achieved without blocking the field of view. Here we simulate an internal calibration system alternative, where a dynamic calibration signal is superimposed on the normal imagery, thus requiring no mechanisms and a smaller size. This method using this type of calibrator shows that when the sensor is pointing at deep space for calibration, it provides an effective non-uniformity correction of the imagery. After performing the proposed method, the NU of the two evaluation images was reduced from the initial 12.99% and 8.72% to less than 2%. Compared to other on-board NUC methods that require an extended reference blackbody source, this proposed approach has the advantages of miniaturization, a short calibration time, and strong adaptability.
Yicheng Sheng; Xiong Dun; Weiqi Jin; Feng Zhou; Xia Wang; Fengwen Mi; Si Xiao. The On-Orbit Non-Uniformity Correction Method with Modulated Internal Calibration Sources for Infrared Remote Sensing Systems. Remote Sensing 2018, 10, 830 .
AMA StyleYicheng Sheng, Xiong Dun, Weiqi Jin, Feng Zhou, Xia Wang, Fengwen Mi, Si Xiao. The On-Orbit Non-Uniformity Correction Method with Modulated Internal Calibration Sources for Infrared Remote Sensing Systems. Remote Sensing. 2018; 10 (6):830.
Chicago/Turabian StyleYicheng Sheng; Xiong Dun; Weiqi Jin; Feng Zhou; Xia Wang; Fengwen Mi; Si Xiao. 2018. "The On-Orbit Non-Uniformity Correction Method with Modulated Internal Calibration Sources for Infrared Remote Sensing Systems." Remote Sensing 10, no. 6: 830.
Current methane gas leak detection technology uses infrared imaging in the medium wave (MW) or long wave (LW) bands, essentially applying cooled infrared detectors. In this study, a simplified three-layer radiative transfer model is adopted based on methane gas detection theory, considering background radiation, atmospheric infrared absorption, gas absorption, and emission characteristics to analyze the contrast of methane gas thermography in different infrared bands. The analysis results suggest that under certain conditions, the 6.6–8.6 μm LW band provides higher contrast compared to the 3–5 μm MW band. The optimal imaging wavelength band is selected according to imaging contrast advantages and disadvantages, and infrared optical systems and infrared filters are designed and optimized. We build a passive methane gas leak detection system based on uncooled infrared focal plane array detectors. By collecting gas images under different conditions, the imaging detection capabilities for methane gas leaks in the MW and LW bands in a laboratory environment are compared. Finally, the developing trends in methane gas detection technology are analyzed.
Zhang Xu; Weiqi Jin; Li Li; Xia Wang; Ji Chen; Yuchao Jia. Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array. Applied Optics 2018, 57, 3991 -4001.
AMA StyleZhang Xu, Weiqi Jin, Li Li, Xia Wang, Ji Chen, Yuchao Jia. Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array. Applied Optics. 2018; 57 (15):3991-4001.
Chicago/Turabian StyleZhang Xu; Weiqi Jin; Li Li; Xia Wang; Ji Chen; Yuchao Jia. 2018. "Band optimization of passive methane gas leak detection based on uncooled infrared focal plane array." Applied Optics 57, no. 15: 3991-4001.
Shuo Li; Weiqi Jin; Li Li; Yiyang Li. An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization. Infrared Physics & Technology 2018, 90, 164 -174.
AMA StyleShuo Li, Weiqi Jin, Li Li, Yiyang Li. An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization. Infrared Physics & Technology. 2018; 90 ():164-174.
Chicago/Turabian StyleShuo Li; Weiqi Jin; Li Li; Yiyang Li. 2018. "An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization." Infrared Physics & Technology 90, no. : 164-174.
The existing methods for shape measurement using polarization of transparent objects are based on two assumptions: (1) the paraxial assumption, assuming that the reflected ray is parallel to the optical axis of the imaging system; and (2) the s-component approximation assumption, which assumes that the s-component of the reflected light is predominant and the p-component is neglected. To overcome limitations posed by these two assumptions, this paper proposes a method based on the polarization characteristics of reflection from a transparent surface and vector operation. To overcome the paraxial assumption, the normal vector of the transparent surface is deduced by vector operation, analyzing the relationships between the direction vector of reflection, the normal vector of the reflection plane, the intersection line of the reflection plane and imaging plane, and the normal vector of the transparent surface. To overcome the limitations of the s-component approximation assumption, the angle between the s-component and the polarization direction of the reflected light is analyzed, which yields improved measurement precision. An experiment was performed with transparent targets (flat glass positioned at different angles), and the results show that the measurement error with this method is significantly less than those of existing methods. Thus, we believe this method overcomes the abovementioned limitations while also improving measurement precision.
Jing Liu; Xiaotian Lu; Weiqi Jin; Xia Wang; Su Qiu; Renjie Wen. Transparent surface orientation from polarization imaging using vector operation. Applied Optics 2018, 57, 2306 -2313.
AMA StyleJing Liu, Xiaotian Lu, Weiqi Jin, Xia Wang, Su Qiu, Renjie Wen. Transparent surface orientation from polarization imaging using vector operation. Applied Optics. 2018; 57 (9):2306-2313.
Chicago/Turabian StyleJing Liu; Xiaotian Lu; Weiqi Jin; Xia Wang; Su Qiu; Renjie Wen. 2018. "Transparent surface orientation from polarization imaging using vector operation." Applied Optics 57, no. 9: 2306-2313.
Jin Zhu; Weiqi Jin; Li Li; Zhenghao Han; Xia Wang. Multiscale infrared and visible image fusion using gradient domain guided image filtering. Infrared Physics & Technology 2018, 89, 8 -19.
AMA StyleJin Zhu, Weiqi Jin, Li Li, Zhenghao Han, Xia Wang. Multiscale infrared and visible image fusion using gradient domain guided image filtering. Infrared Physics & Technology. 2018; 89 ():8-19.
Chicago/Turabian StyleJin Zhu; Weiqi Jin; Li Li; Zhenghao Han; Xia Wang. 2018. "Multiscale infrared and visible image fusion using gradient domain guided image filtering." Infrared Physics & Technology 89, no. : 8-19.