We proposed and demonstrated a high data rate ultraviolet communication system based on a 266nm UV LED array with 50mW luminous power. The emitting source is driven by a three outputs constant-current control circuit, whose driving speed is up to 2Mbps. At the receiving side, in order to achieve the amplification for high-speed signal, a two-stage differential preamplifier is designed to make I-V conversion. The voltage-current gain is up to 140dB and bandwidth is 1.9MHz. An experiment is conducted to test the performance of the UV communication system. The effects of elevation angles and transmission distance are analyzed. It is shown that the ultraviolet communication system has high data rate of up to 921.6kbps and bit error rate of less than 10<sup>-7 </sup>in 150m, which can beat the best record created by UV-LED communication system in terms of the transmission rate.
Using Landsat-7 ETM remote sensing data, the inversion of spectral reflectance of green wheat in visible and near infrared waveband in Yingke, China is studied. In order to solve the problem of lower inversion accuracy, custom atmospheric conditions method based on moderate resolution transmission model (MODTRAN) is put forward. Real atmospheric parameters are considered when adopting this method. The atmospheric radiative transfer theory to calculate atmospheric parameters is introduced first and then the inversion process of spectral reflectance is illustrated in detail. At last the inversion result is compared with simulated atmospheric conditions method which was a widely used method by previous researchers. The comparison shows that the inversion accuracy of this paper’s method is higher in all inversion bands; the inversed spectral reflectance curve by this paper’s method is more similar to the measured reflectance curve of wheat and better reflects the spectral reflectance characteristics of green plant which is very different from green artificial target. Thus, whether a green target is a plant or artificial target can be judged by reflectance inversion based on remote sensing image. This paper’s research is helpful for the judgment of green artificial target hidden in the greenery, which has a great significance on the precise strike of green camouflaged weapons in military field.
The pixels of a retina-like sensor are arranged in concentric rings, and the output image is given in log-polar coordinates. Thus, additional residual errors will not be produced when the output image is rotated. Therefore, retina-like sensors have obvious advantages and many prospects for applications in the fields of image rotation and rapid image rotation-elimination. In this study, a theory concerning the image rotation of a retina-like sensor is proposed, and a solution based on the theory is presented and realized for eliminating image rotation caused by camera rotation. The camera rotation angle is obtained using a microelectromechanical systems digital accelerometer and gyroscope; only the readout sequence of each row from static random-access memory must be changed to achieve image rotation-elimination. Several image rotation-elimination experiments have been performed which show that the proposed solution is simple, accurate, and rapid. This rapid image rotation-elimination method can be used in fields that require higher image rotation-elimination processing speeds.
The purposes of spacecraft vacuum thermal test are to characterize the thermal control systems of the spacecraft and its component in its cruise configuration and to allow for early retirement of risks associated with mission-specific and novel thermal designs. The orbit heat flux is simulating by infrared lamp, infrared cage or electric heater. As infrared cage and electric heater do not emit visible light, or infrared lamp just emits limited visible light test, ordinary camera could not operate due to low luminous density in test. Moreover, some special instruments such as satellite-borne infrared sensors are sensitive to visible light and it couldn’t compensate light during test. For improving the ability of fine monitoring on spacecraft and exhibition of test progress in condition of ultra-low luminous density, night vision imaging system is designed and integrated by BISEE. System is consist of high-gain image intensifier ICCD camera, assistant luminance system, glare protect system, thermal control system and computer control system. The multi-frame accumulation target detect technology is adopted for high quality image recognition in captive test. Optical system, mechanical system and electrical system are designed and integrated highly adaptable to vacuum environment. Molybdenum/Polyimide thin film electrical heater controls the temperature of ICCD camera. The results of performance validation test shown that system could operate under vacuum thermal environment of 1.33×10<sup>-3</sup>Pa vacuum degree and 100K shroud temperature in the space environment simulator, and its working temperature is maintains at 5℃ during two-day test. The night vision imaging system could obtain video quality of 60lp/mm resolving power.
For a new kind of retina-like senor camera and a traditional rectangular sensor camera, dual cameras acquisition and display system need to be built. We introduce the principle and the development of retina-like senor. Image coordinates transformation and interpolation based on sub-pixel interpolation need to be realized for our retina-like sensor’s special pixels distribution. The hardware platform is composed of retina-like senor camera, rectangular sensor camera, image grabber and PC. Combined the MIL and OpenCV library, the software program is composed in VC++ on VS 2010. Experience results show that the system can realizes two cameras’ acquisition and display.
Infrared texture is an important feature in identifying scenery. To simulate infrared image texture effectively at different distances, we propose a model of infrared image texture generation based on scenery space frequency and the image pyramid degradation principle. First, we build a spatial frequency filter model based on imaging distance, taking into account the detector’s maximum spatial frequency, and use the filter to process a “zero” distance infrared image texture. Second, taking into consideration the actual temperature difference of the scenery’s details due to variation of the imaging distance and the effect of atmospheric transmission, we compare the actual temperature difference with the minimum resolvable temperature difference of the thermal imaging system at a specific frequency and produce a new image texture. The results show that the simulated multiresolution infrared image textures produced by the proposed model are very similar (lowest mean square error=0.51 and highest peak signal-to-noise ratio=117.59) to the images captured by the thermal imager. Therefore, the proposed model can effectively simulate infrared image textures at different distances.
For a new kind of retina-like senor camera, the image acquisition, coordinates transformation and interpolation need to be realized. Both of the coordinates transformation and interpolation are computed in polar coordinate due to the sensor’s particular pixels distribution. The image interpolation is based on sub-pixel interpolation and its relative weights are got in polar coordinates. The hardware platform is composed of retina-like senor camera, image grabber and PC. Combined the MIL and OpenCV library, the software program is composed in VC++ on VS 2010. Experience results show that the system can realizes the real-time image acquisition, coordinate transformation and interpolation.
Readout circuit is designed for a special retina-like CMOS image sensor. To realize the pixels timing drive and readout of the sensor, the Altera's Cyclone II FPGA is used as a control chip. The voltage of the sensor is supported by a voltage chip initialized by SPI with AVR MCU system. The analog image signal outputted by the sensor is converted to digital image data by 12-bits A/D converter ADS807 and the digital data is memorized in the SRAM. Using the Camera-link image grabber, the data stored in SRAM is transformed to image shown on PC. Experimental results show the circuit works well on retina-like CMOS timing drive and image readout and images can be displayed properly on the PC.
Retina-like sensor is a kind of anthropomorphic visual sensor, which mimic the distribution of photoreceptors in the human retina. They are applied in fields of machine vision and target tracking. However, there are few reports on retina-like sensor used for forward-motion imaging. During forward-motion imaging, as the objects being imaged move along the optical axis direction during the integration time, image quality becomes worse towards the border of the image. In order to get clearer image, retina-like sensor are trying to be designed based on the feature of forward-motion imaging. In this paper, firstly, the degraded law of rectilinear sensor used for forward-motion imaging is analyzed, the retina-like sensor model based on the feature of forward-motion imaging are proposed. Secondly, the output image of retina-like sensor and rectilinear sensor used during the forward-motion imaging for different scenes at different degeneration degrees are simulated, respectively. Thirdly, the simulated images of both two sensors are assessed by four different image quality assessment methods including visual information fidelity (VIF), complex wavelet structural similarity index (CW-SSIM), Gabor filtered image contrast similarity (GFCS) and peak signal to noise ratio (PSNR), besides, the data amount of two sensors are compared. Four image quality assessments all demonstrate that image quality of retina-like sensor based on the feature of forward motion imaging is superior to that of rectilinear sensor.
The retina-like sensor is a kind of anthropomorphic visual sensor. It plays an important role in both biological and machine vision due to its advantages of high resolution in the fovea, a wide field-of-view, and minimum pixel count. The space-variant property of the sensor makes it difficult to directly measure its modulation transfer function (MTF). The MTF of a retina-like sensor is measured with the bar-target pattern method. According to the pixel arrangement, the sensor is divided into rings and the MTF of each ring is measured using spoke targets with different periods. Comparison between the measured MTF and the theoretical MTF of the sensor showed that they coincide. The differences between them are also analyzed and discussed. The measured MTF helps to analyze the performance of an imaging system containing a retina-like sensor.
KEYWORDS: Quantization, Fringe analysis, Fourier transforms, Error analysis, Signal to noise ratio, Commercial off the shelf technology, Signal processing, Digital filtering, Image quality, Optical engineering
Newton’s rings fringe pattern is often encountered in optical measurement. The digital processing of the fringe pattern is widely used to enable automatic analysis and improve the accuracy and flexibility. Before digital processing, sampling and quantization are necessary, which introduce quantization errors in the fringe pattern. Quantization errors are always analyzed and suppressed in the Fourier transform (FT) domain. But Newton’s rings fringe pattern is demonstrated to be a two-dimensional chirp signal, and the traditional methods based on the FT domain are not efficient when suppressing quantization errors in such signals with large bandwidth as chirp signals. This paper proposes a method for suppressing quantization errors in the fractional Fourier transform (FRFT) domain, for chirp signals occupies little bandwidth in the FRFT domain. This method has better effect on reduction of quantization errors in the fringe pattern than traditional methods. As an example, a standard Newton’s rings fringe pattern is analyzed in the FRFT domain and then 8.5 dB of improvement in signal-to-quantization-noise ratio and about 1.4 bits of increase in accuracy are obtained compared to the case of the FT domain. Consequently, the image quality of Newton’s rings fringe pattern is improved, which is beneficial to optical metrology.
Based on the aliasing theory of focal plane array (FPA) thermal imaging systems, aliasing as noise (AAN) method and under-sampling system evaluation model based on information theory (EMIT) were analyzed. The aliasing was treated as one kind of noise and introduced into minimum resolvable temperature difference (MRTD) model, and the integral expressing of aliasing signal (IAS) method was proposed to evaluate the impact of aliasing on the performance of thermal imaging systems. IAS method was proved to be able to describe the impact of aliasing grade on the system performance effectively. The three MRTD models with different aliasing evaluation methods were researched contrastively by MRTD test experiment and target detection probability experiment. The MRTD model with IAS method was proved to evaluate the performance of under-sampling thermal imaging systems effectively, and could be used in the performance prediction of thermal imaging systems. In the future, the precision of IAS method will be researched further.
HgCdTe and InGaAs material are able to detect near-shortwave infrared extension. The progress of HgCdTe and InGaAs
material and their performances have been discussed. This article mainly presented three aspects of InGaAs negative
electron affinity (NEA) photocathode and image intensifier which are widely used in near-shortwave infrared devices:
the research status, the possible application prospects and the trend.
Retina-like sensors maximize both field of view and resolution in addition to economizing on pixel count, so they play an important role in both biological and machine vision. A new retina-like sensor model for compensating motion blur introduced by forward motion imaging is proposed. Next, the determination of pixel arrangement of a retina-like sensor according to visual task requirements is formulated into a multiobjective optimization problem. Then, three retina-like sensors are designed to meet different visual task requirements using the particle swarm optimization algorithm. The results are robust and approximate to design criteria.
Discrete sampling is one of the important characteristics of thermal imaging systems and has an important effect on the
target acquisition performance. Based on the study of discrete sampling theory, several discrete sampling evaluation
methods are analyzed, and the aliasing caused by under-sampling is considered as a noise of thermal imaging systems.
The aliasing noise is introduced into MRTD model with system noise. MRTD model with aliasing noise is deduced, and
its validity is verified by simulation experiments. MRTD model with aliasing noise is introduced into MRTD channel
width model. It is future work that the impact of discrete sampling on the general performance of thermal imaging
systems will be researched by MRTD channel width model.
Images associated with underwater imaging systems are normally degraded by the intervening water medium. The
imaging instrument records not only the signal of interest, i.e., the radiance diffusely reflected from underwater target,
but also the radiance scattered into the field of view by water molecule and particulates. In order to improve the system
performance, range gated underwater imaging system is used to enhance image quality and visibility in turbid conditions.
Range gated imaging utilizes time discrimination to improve signal-to-backscattering noise ratio by rejecting
backscattered light from the medium. The range gated underwater imaging system basically consists of a pulsed laser
system, a control and synchronous logics and a high-speed gated camera. Because a laser is a highly coherent light
source, speckle noise results from the randomly constructive or destructive interference of the scattered light rays will
appear in the images obtained from the range gated underwater imaging system. The random granular speckle noise
brings great difficulty for the image processing. So the formation causes of speckle noise are discussed and several
different material objects under standard light source and laser are chosen to carry out speckle noise comparative
analysis. And a multidirectional morphological filtering algorithm for reducing speckle noise is proposed by using the
characteristics of morphology's multi-resolution analysis and fast-computing. In order to evaluate the method
objectively, equivalent number and speckle index are introduced. The experimental results demonstrate that the approach
that is adopted not only can reduce the speckle noise of the image effectively but also can preserve the feature detail
Range gated underwater laser imaging technique can eliminate backscattering noise effectively. While the images
associated with underwater imaging systems are normally degraded seriously by the intervening water medium. And the
speckle noise is especially severe for the reason that we adopt the system based on intensified gate imaging technology.
Well known causes of image degradation underwater include turbidity, particulate matters in the water column, and the
interaction between light and medium as light travels through water. Consequently, using full image formation models to
design restoration algorithms is more complex in water than in air because it's hard to get the values of the model
parameters relating to water properties, e.g., attenuation and scattering coefficients. To improve the quality of the low
signal-to-noise ratio images obtained through range gated laser imaging system, an enhancement algorithm is proposed.
The main purpose of the algorithm proposed for processing underwater images is to filter out unwanted noises and
remain desired signals. This algorithm is based on the principle of the least square error method, which fits discrete
image data to continuous piecewise curves. To simply the fitting of image data, the interval of each row and column is
subdivided into several subintervals. Then a curve is used to fit the image data within the subinterval. To merge two
adjacent lines together, a weighting technique with a linear weighting factor is imposed. A series of experiments are
carried out to study the effects of the algorithm. And the signal-to-noise ratio shows that the proposed algorithm can
achieve high quality enhancement images.
Range-gated underwater laser imaging technique can eliminate most of the backscattering and absorption noise
effectively. It has a range of from 4 to 6 times that of a conventional camera with floodlights in the strongly scattering
waters, which becomes a useful technique in oceanic research, deep-sea exploration, underwater remote control and
robotic works. While because of the laser pulse stretching, the image obtained through range gated underwater imaging
system has obvious nonuniformly illuminated character, such as brighter center and darker edge. Low contrast and
grayish white of the image also bring great difficulty for processing. In order to adjust the lightness of the nonuniformly
illuminated image of range-gated underwater imaging system, the water degradation is assumed as illumination variation
and retinal-cortex theory based on color constancy is introduced. Frame integral algorithm has to be applied first to
eliminate system noise for the reason that we adopt the system based on intensified gate imaging technology. And gray
stretch ensures that we can attain appropriate output. In retinal-cortex models, McCann model and McCann-Frankle
model have obvious effect. So we choose the two models for comparison and improve the second one considering the
exponential characteristics of eyes for illumination. In order to evaluate the methods objectively, strength uniformity of
signals is applied. The experimental results demonstrate that the approaches we adopted are all effective and can enhance
the image contrast. And the improved McCann-Frankle model gets more satisfying visual effect.
Scene Classification refers to as assigning a physical scene into one of a set of predefined categories. Utilizing the
method texture feature is good for providing the approach to classify scenes. Texture can be considered to be repeating
patterns of local variation of pixel intensities. And texture analysis is important in many applications of computer image
analysis for classification or segmentation of images based on local spatial variations of intensity. Texture describes the
structural information of images, so it provides another data to classify comparing to the spectrum. Now, infrared thermal
imagers are used in different kinds of fields. Since infrared images of the objects reflect their own thermal radiation,
there are some shortcomings of infrared images: the poor contrast between the objectives and background, the effects of
blurs edges, much noise and so on. Because of these shortcomings, it is difficult to extract to the texture feature of
In this paper we have developed an infrared image texture feature-based algorithm to classify scenes of infrared images.
This paper researches texture extraction using Gabor wavelet transform. The transformation of Gabor has excellent
capability in analysis the frequency and direction of the partial district. Gabor wavelets is chosen for its biological
relevance and technical properties In the first place, after introducing the Gabor wavelet transform and the texture
analysis methods, the infrared images are extracted texture feature by Gabor wavelet transform. It is utilized the
multi-scale property of Gabor filter. In the second place, we take multi-dimensional means and standard deviation with
different scales and directions as texture parameters. The last stage is classification of scene texture parameters with least
squares support vector machine (LS-SVM) algorithm. SVM is based on the principle of structural risk minimization
(SRM). Compared with SVM, LS-SVM has overcome the shortcoming of higher computational burden by solving linear
equations, and has been widely used in classification and nonlinear function estimation. Some experimental results are
given in the end. The result shows that Gabor wavelet transform is successful to extract the texture feature of infrared
image. Compared with other methods the method mentioned in this paper reduces the probability of recognition and
enhances the robustness.
All objects emit radiation in amounts related to their temperature and their ability to emit radiation. The infrared image
shows the invisible infrared radiation emitted directly. Because of the advantages, the technology of infrared imaging is
applied to many kinds of fields. But compared with visible image, the disadvantages of infrared image are obvious. The
characteristics of low luminance, low contrast and the inconspicuous difference target and background are the main
disadvantages of infrared image. The aim of infrared image enhancement is to improve the interpretability or perception
of information in infrared image for human viewers, or to provide 'better' input for other automated image processing
Most of the adaptive algorithm for image enhancement is mainly based on the gray-scale distribution of infrared image,
and is not associated with the actual image scene of the features. So the pertinence of infrared image enhancement is not
strong, and the infrared image is not conducive to the application of infrared surveillance. In this paper we have
developed a scene feature-based algorithm to enhance the contrast of infrared image adaptively. At first, after analyzing
the scene feature of different infrared image, we have chosen the feasible parameters to describe the infrared image. In
the second place, we have constructed the new histogram distributing base on the chosen parameters by using Gaussian
function. In the last place, the infrared image is enhanced by constructing a new form of histogram. Experimental results
show that the algorithm has better performance than other methods mentioned in this paper for infrared scene images.
As a fundamental image processing operation, a good denoising method should keep the original image information as
much as possible. However, most denoising methods may degrade or remove the fine details and texture of the original
image. In this paper, a force field method is adopted to transform the image pixels within a local window into a potential
energy surface and then to distinguish the image edges and the noises in this potential energy field. Afterwards, different
templates are used according to the judgment and the adaptive filter is applied to the local pixels respectively. This new
method has less computational complexity than the other algorithms of transform domain, which means it can be
implemented in a real-time processing system. Also the new method can preserve more image edges than the traditional
filters. Finally the performance of the proposed method is compared in this paper with other popular methods by using
evaluation criterion of SNR and SSIM(a measure of structural similarity). The results show that the proposed method is
reliable and especially helpful to preserve the image details.
This paper describes a design of sun-tracking warning demonstration system in solar blind UV. After analyzing of the
system structure and guide line of the sun-tracking warning system in solar blind UV, the key techniques of the
sun-tracking UV warning system are discussed and designed, including the optical system, UV filter module, optical
modulation system, UV detectors and its sun-tracking servo. A total reflect Cassegrain UV optical system with simple
structure, reliable performance and high-quality imaging ability is designed and manufactured. In order to enhance the
received SNR and process the signal easily, an optical UV filter and an optical modulation reticle are used to filter and
modulate the target's direct signals to alternating signal. Functional experiments show that sun-tracking warning system
needs better UV filter module whose total stopband rejection should be higher than 10<sup>-10</sup>.
A 2-D model is developed for the simulation. Calculations take into account the chemiluminence reaction of CO-O,
which is the dominant sources of radiation in the UV wavelength band considered, and particle emission/scattering
effects produced by alumina particles. The alumina particle is considered as a discrete phase through the continuous
flow, assumed to be in solid state with diameters ranging from 5 micron to 17 micron. The atmospheric effects, pressure
and temperature, are included in the boundary condition. Four cases, altitudes at 0km, 4km, 15km and 30km are
calculated separately, and comparisons are made with each other .Finally, the analysis of affecting factors is presented.
Solar blind UV intensified CCD (ICCD) has been widely applied in solar blind UV detection by the advantages of
imaging, high sensitivity, photon counting, fast speed of response, large dynamic range, low cost, mature technology and
so on. Solar blind UV ICCD consists of UV optical aperture with UV filter, photocathode, micro-channel plate (MCP),
phosphor, optical coupling and CCD. The study of solar blind ICCD detection performance starts from the target
imaging characteristic. Then the expression of ICCD output SNR is obtained based on the analysis of distributing the
image intensifier noise and CCD noise. The detection probability and false alarm probability are expressed by the
normal distribution, which are depended on the ICCD output SNR and threshold SNR. A new ICCD detection range
model is developed that takes into account ICCD output SNR, threshold SNR, detection probability and false alarm. In
according to the study of detection performance, the solution of improving the ICCD detection performance is given.
Infrared images often display in gray scale. The low contrast and the unclear visual effect are the most notable characters
of infrared images that make difficult to observe. It is a fact that gray scale is not sensitive to human eyes, and it has only
60 to 90 just noticeable differences (JNDs). In comparison with gray scale, color scale might give up to 500 JNDs.
Usually people can distinguish many kinds of colors much more than grays. And in gray images, human don't have the
ability to tell apart the nuances about detail. Pseudo-color coding enhancement is the task of applying certain alterations
to an input gray-image such as to obtain color-image that is a more visually pleasing. In this paper, we introduced a
pseudo-color coding method based on human vision system for infrared images display. The HSI space is especially fit
for human vision system and is viewed as an approximation of perceptual color space. So the pseudo-color coding
method introduced is based on HSI space. In the first place, the individual functional relationship of Hue, Intensity, and
Saturation with gray scale level is established. In the second place, the corresponding RGB values are obtained through
transformation from the HSI color space to the RGB space. Lastly, the effect of Infrared images enhancement based on
the pseudo-color coding method is displayed. Results indicate that this method is superior to other methods through the
Image intensifier and intensified CCD (ICCD) are critical components in the field of night vision technology. There are some specifications, such as luminance uniformity, fixed pattern noise, resolution, modulation transfer function (MTF), etc., which can be used to evaluate the performance of such components. A digitally integrated test system for performance evaluation of image intensifier and ICCD is described in this paper. The system can test 11 specifications for imaging intensifier (generation 1, 2 and 3) and ICCD with some essential accessories. The system operation theory, structure and testing results are represented in detail. The system has been run at North Night Vision Technology Co. for about 10 months. The results after long running period are given. And the factors that affect the measurement accuracy are analyzed. The results show that the digitally integral system has high measurement precision and stability.
With the development of UV missile warning systems, there is a need to assess or predict the UV signature for missile. This paper shows an emission model for UV missile plume signature. The model computes the missile plume flow field distribution, takes into account CO-O chemiluminescence and hot particles emission in the plume, and analyses the influences of the alumina particles scattering. Plume flow field is computed by the RNG k-ε turbulence model with
non-equilibrium wall functions. Alumina particles optical properties are calculated by using Mie theory and the particles are assumed a log-normal size distribution. Radiative transfer equation is solved by the discrete-ordinates method. The model is applied to a user-defined test case and compared with other UV plume emission signature
models based on different algorithms, the result of comparison is coincident and satisfied.
A new method is proposed for the 3D (three-dimensional) image restoration of the wide-field microscope based on the MPMAP algorithm (Poisson-MAP Super-resolution image restoration algorithm with Markov constraint) according to the 3D features of the microscopic image. The neighborhood of the Markov random field in MPMAP algorithm is extended to 3D, and the regularization parameter α of the bound term in MPMAP is simplified. As a result, the restoration of 3D image of wide-field microscope is achieved, and the more perfect effect of the image restoration is got. When images within noise are restored by different value α, different attainable resolution and signal-to-noise ratio (SNR) in the restored image. Experiment results show that it is necessary to select appropriately value of α, and take tradeoff between resolution and SNR in the restored image so that the more perfect effect of the image restoration is got.
Since the Loophole Photovoltaic Detector was designed by some researchers, some studies of the theoretic analysis of this new configuration of detectors have been made. In this paper, deduction and analysis of the Optical Transfer Function(OTF) are discussed concerning the following three kinds of detectors, the Rectangular Photovoltaic Unit Detector, the Cylindrical Photovoltaic Unit Detector and the Loophole Photovoltaic Unit Detector. The OTFs are deduced on the basis of opto-electrical imaging theory. The Fourier Transform and some other mathematical methods are used herein. According to the comparison among these three different detectors' OTF expressions, a conclusion is shown that the loophole photovoltaic unit detector has an advantage in spatial imaging characteristics. The loophole photovoltaic unit detector has much higher spatial resolution than the rectangular photovoltaic unit detector. By a mass of computations, another conclusion is shown that the spatial opto-electrical imaging characteristics of Loophole Photovoltaic Unit Detectors are influenced by its geometrical size. The higher spatial resolution is gained in those Loophole Photovoltaic Unit Detectors with smaller size.
An innovative Fourier Transform hyperspectral imaging system based on reflective optics is currently being studied. It can record both spatial images and spectral information of a sample instantaneously. Substantial properties of the sample can be elucidated from such images. Compared to classical Imaging Spectrometer using lenses and prisms, the significant characteristic of this system is that it only uses reflective mirrors and just one beam splitter. Such structure will help to largely avoid the limitation of spectral range and the refraction non-homogenize both of which affect the quality of imaging. Therefore, the noticeable advantages of this system are high signal-to-noise ratio, high spatial and spectral resolution, large spectral bandwidth, high throughput, non-chromatic aberration and very compact optical structure in which just one imaging system could applicable to a rather wide spectral bandwidth. This project includes both theoretical analysis and development of an experimental instrument. With the instrument, the images that contain one-dimensional spatial image and another dimensional interferogram are already collected. The data processing system could transform the interferogram of each scene to its spectral information. The typical experimental results are given in this paper.
Construct the transform function model of low-light-level night vision imaging system and its components; Convert the input image with a certain pattern through FT to get the frequency spectrum of it, and filter the frequency spectrum of input image by use of the transform function model. And then, convert the filtered frequency spectrum of input image through IFT to get the filtered image. Thus, implement the digital simulation of low-light-level night vision imaging system by computer.
Use the transform function theory to analyze the imaging characteristic of photo electronic imaging system, and set up the simulation system for detecting characteristic of it with the high-speed DSP TMS320C6201. Through the simulation, we can evaluate the detecting characteristic of a certain photo electronic imaging system, change its components while simulating, and then compare the characteristic before change with after change to provide intuitionistic reference for optimizing design of photoelectric imaging system.