Infrared polarization technology is generally applied in object detection and analysis. However, chromatic aberration restricted the development of Infrared polarization detectors. Metalenses are two-dimensional artificial electromagnetic materials to balance chromatic aberration and an ideal platform for miniaturization and integration of infrared polarization technology. In this paper, a fully polarized detection of mid-infrared achromatic metalens is designed, with a single metalens unit diameter of 30μm, a focal length of 15μm, and a working wavelength of 3μm-5μm. Through FDTD software simulation, the results show that the metalens focuses at focal plane for any polarized state light throughout the working wavelength band, with a full width at half maximum (FWHM) of the peak of less than 6&μm, achieving achromaticity. The maximum aspect ratio of the nanopillar is 15:1, meeting the requirements of electron beam lithography processing. The designed metalens achieves full-polarization detection a wider working wavelength band comparing with existing polarization detection devices, which indicates a potential application value for mid-infrared polarization detection and imaging technology.
Most industrial gases such as methane(CH4), ethylene (C2H4) and sulfur hexafluoride (SF6) have obvious absorption characteristics in the infrared band. The infrared absorption spectrum of leaking gas can be obtained through multispectral or hyper-spectral detection technologies to realize gas identification. However, these methods need a lot of work calibrating the detector response curve to target gas. In this work, a sparse infrared absorption spectrum based support vector machine (SVM) recognition method is proposed to obtain the gas absorption peak information without response curve calibration. An uncooled infrared imaging component is utilized to compose a multi-broadband long-pass differential filter infrared imaging setup that filters in the range of 7.5μm ~13.5 μm. Data extracted from multi-band infrared images of C2H4 and SF6 collected by the setup, combined with the simulated data generated by the simulated sparse spectrum algorithm, constitute training set to SVM. C2H4 and SF6 can be accurately identified under laboratory conditions with the path-concentration of 500 ppm·m ~1000 ppm·m. The easy to implement and cost-effective method is expected to realize real-time identification of leaking gas.
The dual-band spectral differential (DB-SD) infrared gas imaging system adopts two wideband longwave-pass filters, the non-overlapping spectral region of the two filters are located at the strong absorption peak of the gas, and the differential images are obtained by subtracting between those two filtered images. Wideband longwave-pass filters can ensure high irradiance. While the differential processing is equivalent to a narrow-band filter, which can enhance the contrast between gas and background, thus effectively improving the gas detection capability of the thermal imager. However, differential processing inevitably accumulates random noise, resulting in the deterioration of image quality. In addition, for differential images with small gas leakage, there are still some problems, such as weak contrast and unclear boundary. Therefore, this paper aims at denoising and enhancement differential images. Considering the temporal redundancy and gas motion characteristics of differential image sequence, a 3D spatiotemporal filtering denoising algorithm based on approximately K-nearest neighbor patch matching and optical flow is proposed to improve the image quality. In addition, gas contrast enhancement algorithm based on variance statistical characteristics is proposed to highlight the gas region, which is equivalent to improving the gas detection capability of DB-SD imaging systems.
Quantum dots have been considerred to be suitable candidates for down-shifting applications. The integration of quantum dots with Si photodetector provide low cost method to extend the reponse in the UV region. However, the lack of suitable processing technique reduce the reposne in visible region. In this work, we firstly report the integration of in-situ fabricated perovskite quantum dots embedded composite films (PQDCF) as down-shifting materials for enhancing the ultraviolet (UV) response of silicon (Si) photodetectors toward broadband and solar-blind light detection. External quantum efficiency measurements show that the UV response of PQDCF coated Si photodiodes greatly improved from near 0% to at most of 50.6±0.5% @ 290 nm. As compared to the calculated maximum value of 87%, the light coupling efficiency of the integrated device is determined to be 80%@395 nm, suggesting an efficient down-shifting process. Furthermore, PQDCF was also successfully adapted for electron multiplying charge coupled device (EMCCD) based image sensor. The PQDCF coated EMCCD shows linear response with high-resolution imaging under illumination at 360 nm, 620 nm and 960 nm, implying the ability of broadband light detection in the UV, visible (VIS) and near infrared (NIR) region. Furthermore, a solar-blind UV detection was demonstrated by integrating a solar-blind UV filter with PQDCF coated EMCCD. In all, the use of PQDCF as luminescent down-shifting materials provides an effective and low-cost way to improve the UV response of Si photodetectors.
Silicide Schottky-barrier midwave infrared detectors for the 3 to 5 μm waveband typically use a 2 to 8 nm metal-silicide layer grown on silicon substrates as an absorption layer. We demonstrate the use of an SiO2-film-coated subwavelength grating as an antireflection incident plane in such detectors to enhance absorption at the 3 to 5 μm waveband in the metal-silicide layer for improving the external quantum efficiency (EQE). Taking a PtSi/p-Si structure as an example, we fabricate samples and build a test platform to characterize the EQE of a PtSi/p-Si Schottky-barrier detector. Simulation results show that low reflection efficiency (<9%) for the subwavelength-grating incident plane and factors of 1.5 to 1.8 enhancement in absorption of the PtSi layer are achieved at normal incidence across the 3 to 5 μm waveband. Measurement results show that this increase translates into factors of 1.3 to 1.7 enhancement in EQE. This improvement in EQE results from absorption enhancement due to antireflection effects and the forward scattering of incident infrared radiation in the subwavelength grating, which increases the effective optical path in the detector. The results also suggest that fabricating a subwavelength-grating incident plane is a general, low-cost method to enhance EQE in various infrared material platforms used for back-illuminated detectors.
Motion detection frequently employs Optic Flow to get the velocity of solid targets in imaging sequences. This paper suggests calculate the gas diffusion velocity in infrared gas leaking videos by optic flow algorithms. Gas target is significantly different from solid objects, which has variable margin and gray values in diffusion. A series of tests with various scenes and leakage rate were performed to compare the effect of main stream methods, such as Farneback algorithm, PyrLK and BM algorithm. Farneback algorithm seems to have the best result in those tests. Besides, the robustness of methods used in uncooled infrared imaging may decline seriously for the low resolution, big noise and poor contrast ratio. This research adopted a special foreground detection method (FDM) and spectral filtering technique to address this issue. FDM firstly computes corresponding sample sets of each pixel, and uses the background based on the sets to make a correlation analysis with the current frame. Spectral filtering technique means get two or three images in different spectrum by band pass filters, and show a better result by mixing those images. In addition, for Optic Flow methods have ability to precisely detect directional motion and to ignore the nondirectional one, these methods could be employed to highlight the gas area and reduce the background noise. This paper offers a credible way for obtaining the diffusion velocity and resolves the robust troubles in practical application. In the meanwhile, it is an exploration of optic flow in varied shape target detection.
KEYWORDS: Near infrared, Color imaging, Imaging systems, Optical filters, Image fusion, Cameras, Visible radiation, Spectroscopes, Solar radiation, RGB color model
The near infrared radiation is the main component of the solar radiation. It's widely used in the remote sensing, nightvision, spectral detection et al. The NIR images are usually monochromatic, while color images are benefit for scene reconstruction and object detection. In this paper a new computed color imaging method based on the neighborhood statistics lookup table for NIR and visible was presented, and its implementation system was built. The neighborhood statistics lookup table was established based on the neighborhood statistical properties of the image. The use of the neighborhood statistical properties can enriched the color transmission variables of the gray image. It obtained a colorful lookup table that could improve the effects of the color transfer and make the colorized image more natural. The proposed lookup table could also transfer the color details well for the neighborhood statistical information representing the texture of the image. The results shows that this method yields a color image with natural color appearance and it can be implemented in real-time.
For visible and infrared color fusion images of three typical scenes, color harmony computational models are proposed to evaluate the color quality of fusion images without reference images. The models are established based on the color-combination harmony model and focus on the influence of the color characteristics of typical scenes and the color region sizes in the fusion image. For the influence of the color characteristics of typical scenes, color harmony adjusting factors for natural scene images (green plants, sea, and sky) are defined by measuring the similarity between image colors and corresponding memory colors, and that for town and building images are presented based on the optimum colorfulness range suited for a human. Simultaneously, considering the influence of color region sizes, the weight coefficients are established using areas of the color regions to optimize the color harmony model. Experimental results show that the proposed harmony models are consistent with human perception and that they are suitable to evaluate the color harmony for color fusion images of typical scenes.
Passive infrared gas imaging systems have been utilized in the equipment leak detection and repair in chemical
manufacturers and petroleum refineries. The detection performance mainly relates to the sensitivity of infrared detector,
optical depth of gas, atmospheric transmission, wind speed, and so on. Based on our knowledge, the spatial concentration
distribution of continuously leaking gas plays an important part in leak detection. Several computational model of gas
diffusion were proposed by researchers, such as Gaussian model, BM model, Sutton model and FEM3 model. But these
models focus on calculating a large scale gas concentration distribution for a great amount of gas leaks above over 100-
meter height, and not applicable to assess detection limit of a gas imaging system in short range. In this paper, a wind
tunnel experiment is designed. Under different leaking rate and wind speed, concentration in different spatial positions is
measured by portable gas detectors. Through analyzing the experimental data, the two parameters σy(x) and σz (x) that
determine the plume dispersion in Gaussian model are adjusted to produce the best curve fit to the gas concentration
data. Then a concentration distribution model for small mount gas leakage in short range is established. Various gases,
ethylene and methane are used to testify this model.
As to visualize the leaking gas cloud which is not visible to the naked eyes, three categories of techniques have emerged,
Backscatter Absorption Gas Imaging, Passive Thermal Imaging, and Imaging Spectrometer. Among these systems,
Signal to Noise Ratio (SNR) is generally used to deduce gas leakage detection limit and leads to several performance
evaluation parameters, such as Noise-Equivalent Spectral Radiance and Noise-Equivalent Concentration-Path Length.
However, in most cases, measuring the SNR accurately is not accessible and usually needs auxiliary instruments.
Therefore, we focus on researching a gas leakage detection model according to the general parameter of a thermal imager,
Noise Equivalent Temperature Difference (NETD). Firstly, the Gas Equivalent Blackbody Temperature Difference
(GEBTD) is obtained by calculating the attenuated radiation of the On-plume path and that of the Off-plume path
respectively. A simplified form of GEBTD was derived by our previous paper, assuming that the work range was short
and the affection of atmospheric transmission was omitted. But in this paper, more factors are considered to establish a
more realistic and accurate detectivity model. The radiation of the gas cloud and the attenuation of the atmosphere are
taken into account as well as the size of the leakage spot which inevitably affects the concentration path length. Secondly,
the NETD and the GEBTD are compared to determine the detection capability. At last, an experiment is designed to
verify the accuracy and reliability of this model on the basis of the gas cloud concentration cone distribution model.
The fingerprint region of most gases is within 3 to 14μm. A mid-wave or long-wave infrared thermal imager is therefore
commonly applied in gas detection. With further influence of low gas concentration and heterogeneity of infrared focal
plane arrays, the image has numerous drawbacks. These include loud noise, weak gas signal, gridding, and dead points,
all of which are particularly evident in sequential images. In order to solve these problems, we take into account the
characteristics of the leaking gas image and propose an enhancement method based on adaptive time-domain filtering
with morphology. The adaptive time-domain filtering which operates on time sequence images is a hybrid method
combining the recursive filtering and mean filtering. It segments gas and background according to a selected threshold;
removes speckle noise according to the median; and removes background domain using weighted difference image. The
morphology method can not only dilate the gas region along the direction of gas diffusion to greatly enhance the
visibility of the leakage area, but also effectively remove the noise, and smooth the contour. Finally, the false color is
added to the gas domain. Results show that the gas infrared region is effectively enhanced.
A local color transfer method based on dark channel dehazing for visible/infrared image fusion is presented. Image
fusion combines complemental information from visible and infrared images. Visible image supplies plenty of scene
details and infrared image is good at popping out hot or cold targets. However, under a bad weather condition, such as
haze or fog, the visible image is degraded greatly and leads to a low contrast and poor color fidelity fused image. Color
transfer can improve the color appearance using a bright haze-free reference image, but it usually modifies the pixel
values according to the global mean value and standard deviation in each color channel. This paper pays more attention
to the dark channel of the reference image and so applies different color transfer schemes to haze area and haze-free area.
Results show that it is effective for decreasing the bad effect of the haze and achieving a more visually pleasing color
visible/infrared fused image.
Leakage of dangerous gases will not only pollute the environment, but also seriously threat public safety. Thermal infrared
imaging has been proved to be an efficient method to qualitatively detect the gas leakage. But some problems are remained,
especially when monitoring the leakage in a passive way. For example, the signal is weak and the edge of gas cloud in the
infrared image is not obvious enough. However, we notice some important characteristics of the gas plume and therefore
propose a gas cloud infrared image enhancement method based on anisotropic diffusion. As the gas plume presents a large
gas cloud in the image and the gray value is even inside the cloud, strong forward diffusion will be used to reduce the noise
and to expand the range of the gas cloud. Frames subtraction and K-means cluttering pop out the gas cloud area.
Forward-and-Backward diffusion is to protect background details. Additionally, the best iteration times and the time step
parameters are researched. Results show that the gas cloud can be marked correctly and enhanced by black or false color,
and so potentially increase the possibility of gas leakage detection.
Standoff detection of gas leakage is a fundamental need in petrochemical and power industries. The passive gas imaging
system using thermal imager has been proven to be efficient to visualize leaking gas which is not visible to the naked
eye. The detection probability of gas leakage is the basis for designing a gas imaging system. Supposing the performance
parameters of the thermal imager are known, the detectivity based on electromagnetic radiation transfer model to image
gas leakage is analyzed. This model takes into consideration a physical analysis of the gas plume spread in the
atmosphere-the interaction processes between the gas and its surrounding environment, the temperature of the gas and
the background, the background surface emissivity, and also gas concentration, etc. Under a certain environmental
conditions, through calculating the radiation reaching to the detector from the camera's optical field of view, we obtain
an entity "Gas Equivalent Blackbody Temperature Difference (GEBTD)" which is the radiation difference between the
on-plume and off-plume regions. Comparing the GEBTD with the Noise Equivalent Temperature Difference (NETD) of
the thermal imager, we can know whether the system can image the gas leakage. At last, an example of detecting CO2 gas by JADE MWIR thermal imager with a narrow band-pass filter is presented.
KEYWORDS: Image fusion, Night vision, Ultraviolet radiation, RGB color model, Infrared imaging, Signal processing, Detection and tracking algorithms, Image processing, Digital signal processing, Thermography
To obtain a color night vision image, we proposed a color transfer algorithm in YUV color space based on the color
transfer algorithm in lαβ color space which Reinhard proposed. After rendering the simple statistics (means and
standard deviations) of the target image to the source image, the color appearance of the target image is transferred
to the source image. 2D chromatic histogram (UV histogram) which can help to find an appropriate target image is
established. Finally, we illustrated several examples of color transfer to multi-band fused images which are fused in
MIT fusion scheme. After a color fused image is obtained, the color transfer is executed to render the color
information of the target image to the fusion image. The final image could have a day-like color appearance.
Besides, the algorithm has less operation than which in lαβ color space because of less transform complexity. It can
be realized in real time in digital signal processors without color space transformation between RGB and YUV.
KEYWORDS: Imaging systems, Modulation transfer functions, Optoelectronics, Charge-coupled devices, Eye, Human vision and color perception, Signal to noise ratio, Sensors, Video, Visual process modeling
The Square Integral Method based on the Minimum Resolvable Contrast (MRC) is to be introduced in this paper as
an evolution for the design and evaluation of optoelectronic imaging systems. It is well known that there exists an optimal
angle magnification which can make optoelectronic imaging systems and human eye matching optimally, so that
optoelectronic imaging systems can performance best. Based on MRC (Minimum Resolvable Contrast) and channel width,
a new method called Square Integral (SQI) method was presented for evaluating the general performance of a CCD imaging
system, and attaining the optimal angle magnification or optimal viewing distance. Results calculated with this method are
in good agreement with the experimental measurements. From the agreement between the practical use and the theoretical
predictions for the variation of CCD size, optical focus, luminance and human vision, it demonstrates that the SQI
method is an excellent universal measure for the optimal angle magnification and the performance of CCD imaging
systems.
A color transfer scheme for visible and infrared images is presented. Two main procedures are included: image fusion
using steerable pyramid in YUV color space, color transfer based on local mean value of infrared image to enhance hot
contrast. Firstly, visible and infrared images are decomposed into 18 subband images with a 4-scale 4-oriatation
steerable pyramid that contains one highpass subands, one lowpass subband and sixteen bandpass subbands. In each
suband image, Y component of the fused image is formed by the pixels whose value is the larger one between the
visible and infrared images. The weighted subtracting operations between visible and infrared constitute the U and V
components. Then, during the process of color transfer, the local gray mean in the 5×5 window of the infrared image is
concerned. The V component that represents the difference between luminance(Y) and red color is increased by the
ratio of the local mean value to the global mean value. Therefore, the hot contrast of infrared is enhanced by rendering
hot targets intense red color. Test results show that, the image fusion with the 4-scale 4-oriatation steerable pyramid
multiples the paths to transfer the color and luminance of a target image into the fused images, thus, the transferred
images are much more colorful, and synchronously reserve the two image's advantage that the visible image is good at
situation awareness and the infrared image is superior in target detection.
Color fusion algorithm for visible and infrared(IR) images based on color transfer in YUV color space under trees, lawn, or land background is presented. Considering the red color will alert observers to possible interested target or danger, this paper aims at working on an algorithm that emphasizes hot targets in IR image with intense red, and the background details in visible image present natural color similar to a color day-time image. V component of YUV space represents the difference between red and Y. Properly increasing the V value will obtain intense red color. Therefore, a nonlinear transfer method based on local mean value of the IR image is proposed. A window of size 5x5 is used to locate hot target in IR image. When the local gray mean value in this window is larger than the global mean value, we determine that this pixel is in a hot area. Then its V value is increased by the ratio of the local gray mean value to the global mean value. Tests show that this method pops out the hot targets with intense red color while the background rendered natural color appearance.
A real-time color transfer system based on 3 pieces of multi-media DSP TM1300 for low-light level
visible(LLLV) and infrared(IR) images is built. Computing quantity is split among three TM13003. Two pieces of
TM1300 preprocess the dual-band images and calculate their mean and standard deviation respectively. The third
TM1300 executes fusion and color transfer in YUV space: Firstly the two preprocessed images are fused into one
primary color image(source image) in which hot targets present warm color, cold targets present cool color. Then the
mean and standard deviation of source images in Y, U, V components are deduced by preprocessed images pixel value
and their mean and standard deviation. Finally, the Y, U and V component of source image are scale by the variation ratio
of a day-time color image(target image) to the source image. The color and luminance distribution of the target image is
transferred into source image and makes it present a sort of day-time color appearance. Comparing to the usually used
l&agr;&bgr; space, color transfer in YUV space can avoid iterative color space transformation, logarithmic and exponential
calculation, and thus be effective in real-time realization while the color transferred results are acceptable.
KEYWORDS: Thermography, Video, Temperature metrology, Image analysis, Databases, Local area networks, Computer programming, Human-machine interfaces, Power supplies, Interfaces
A real-time 16-bit digital video grabber based on USB 2.0 protocol, thermal temperature measurement and dynamic analysis software are presented. One kind of 35 μm square pixel pitch's uncooled focal plane array thermal imaging module with 16-bit digital video output was selected. As long as being equipped with suitable camera lens, power supply and monitor, the module can be integrated as a thermal imaging system for observation, recognition, tracking and thermal images detection. Cypress Corp. CY7C68013 USB protocol chip is utilized. Main developments of video grabber are stressed on data transfer and logic control between imaging module and CY7C68013 with CPLD devices, and programming windows drivers based on Windriver. The measurement and dynamic analysis software involves not only traditional false color coding, point/line/area temperature analysis, but also several new functions: 1. Automatically mark and monitor the area when its temperature is higher than a setting threshold, and plot the curve of temperature histogram against time. 2. Monitor and plot the temperature movement versus time in manually setting points or area. 3. Database based on local area network convenient for sharing and managing data. Statistics form, curve plot, single-frame and sequence images can enter into database by manual operation or in term of some conditions set previously, such as files saving interval. Moreover, different functions are designed according to the authority of accessing local area network.
Color night vision through fusion of images derived from visible and thermal infrared sensors has come into application. A lot of research of perceptual or subjective evaluation of color fusion algorithms is conducted by the TNO, MIT and NRL[1-5]. Objective evaluation is becoming an increasing issue. A good fusion algorithm should preserve or enhance all of the useful features, i.e., targets pop out and content or details from the source images. Objective: The goal of our research is to predict details and target detectability of color fusion images by measuring image contrast. Methods: A color image contrast metric[11], which was designed to compute how much details for natural images, is employed to measure details and target detectability of color fusion images in this paper. A sub-band contrast index is defined, the first band contrast index indicates the level of details, and higher band contrast indexes indicate the level of target detectability. Results: The perceptual details have high correlation with the first sub-band contrast indexes, and the perceptual target detectability has correlation with higher sub-band contrast indexes. This means the sub-band contrast indexes may predict details and target detectability, however, noise effect on details need to be considered and prediction of target detectability need to be improved.
Pyroelectric uncooled focal plane array (FPA) thermal imager has the advantages of low cost, small size, high responsibility and can work under room temperature, so it has great progress in recent years. As a matched technique, the modulate chopper has become one of the key techniques in uncooled FPA thermal imaging system. Now the Archimedes spiral cord chopper technique is mostly used. When it works, the chopper pushing scans the detector's pixel array, thus makes the pixels being exposed continuously. This paper simulates the shape of this kind of chopper, analyses the exposure time of the detector's every pixel, and also analyses the whole detector pixels' exposure sequence. From the analysis we can get the results: the parameter of Archimedes spiral cord, the detector's thermal time constant, the detector's geometrical dimension, the relative position of the detector to the chopper's spiral cord are the system's important parameters, they will affect the chopper's exposure efficiency and uniformity. We should design the chopper's relevant parameter according to the practical request to achieve the chopper's appropriate structure.
Although gray-level fused images can optimally integrate the modalities of low-light CCD and infrared imager, operators cannot tell from which modality the details originate. Thus the fundamental that human eyes can discern much more color categories than gray levels has been used to assigns a distinct color to each sensor modality. But the color fused image which has no natural appearance will fatigue operators greatly. Our approach is building on MIT scheme and aims at achieving natural appearance in the color fused image. MIT scheme derives its basis from biological models of color vision and utilizes the feed-forward center-surround shunting neural network to enhance and fuse low-light and infrared images. We bring forward linear fusion architecture, and composite architecture that comprises the enhancement part of MIT scheme and the linear fusion architecture. Furthermore, enhancement and combination methods for low-light and infrared images of different properties have been specified.
Dual-band uncooled Focal Plane Array (FPA) thermal imaging system adopts an Archimedes spiral cord chopper and a matched dual-band light filter to achieve two single-band IR images in one imaging system. Traditional methods of getting two bands images need two single-band thermal imagers, this system only needs one detector and one optical imaging system, so the system's structure becomes smaller and the cost can be reduced. This paper studies the dualband light filter and the realization of capturing dual bands images, it also researches the algorithm of dual-band temperature measurement, using this algorithm, two bands infrared images can be fused into a temperature image.
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