The tight focused pump beam nonlinear frequency upconversion based on Hadamard coding is presented to acquire converted photon images. The pump beam is optimized by tight focusing to enhance its power
density in nonlinear crystal. In order to reduce the distortion caused by the point spread function effect, the object is encoded by measurement matrices and the converted photons corresponding to each pattern is measured. Thus the converted image with sharp edges can be reconstructed by the measurements and the measurement matrices. In the experiment, the image with 64 × 64 pixels is acquired and the peak of the dark noise is less than0.7photons/spatial/second element for 10 ms measurement time.
Large-array EMCCD requires a complex and large number of drive signals. To solve this problem, this paper designs a large-array EMCCD drive circuit system, which uses large-scale integrated circuit FPGA to generate EMCCD’s timing signal, multiplication signal and DC bias signal, using Verilog language for hardware description, and using the integrated AD chip to sample the analog output signal of EMCCD. Then use the idea of "ping-pong" operation to control DDR3 to complete the splicing of multi-channel digital images. Finally, based on the KAE-02150 EMCCD chip produced by ON Semi, the design of a large-area internal line transfer EMCCD camera was realized.
Electron-Multiplying Charge Coupled Device (EMCCD) is an all-solid-state low-light imaging device in the true sense, and it is an emerging device. Its high sensitivity, all-weather imaging and other technical characteristics have very important applications in military, astronomy and other fields. Based on the working principle of EMCCD, this paper analyzes the principle of noise generation and the countermeasures of the imaging system, and proposes an efficient EMCCD imaging system design method. We choose the Kintex-7 series FPGA of Xilinx Company as the core processing unit, and designed related drive circuits, acquisition circuits, storage circuits and communication circuits. The performance of the module is verified by driving CCD201 of E2V Company, and the signal-to-noise ratio of the module is tested and analyzed. The results show that the EMCCD imaging system in this paper has good low-noise performance
MRTD (Minimum Resolvable Temperature Difference) is an important parameter for comprehensive evaluation of temperature resolution and spatial resolution of infrared imaging systems. It has become one of the necessary detection parameters for manufacturers of thermal imaging cameras. The traditional subjective MRTD parameter test method is gradually replaced by objective test methods due to its long test time and high labor cost. At present, the objective test method has developed the video MTF method and the photometric camera method, but both methods have their corresponding limitations. This paper proposes a new objective MRTD parameter test method based on CNN neural network. Firstly, the four-bar target image used to test the MRTD parameters is analyzed. It is concluded that the process of testing the MRTD parameters is essentially an image classification, which lays a foundation for the learning of CNN neural networks. Then the network model of CNN neural network interpretation of four-bar target image is expounded, and the accuracy of MRTD test results under different network models is analyzed. It was found that the network structure should not be complicated in the classification process of the four-bar target image. Based on the classic CNN neural network LeNet model, this paper proposes a CNN neural network suitable for four-bar target image classification problem by optimizing the convolution layer size, changing the activation function and adjusting the network structure. The experimental results show that the optimized CNN neural network improves the accuracy and repeatability of the MRTD parameter test.
Introduces a real-time color imaging system can be operated at night and uses a low-cost, simple and convenient CMOS sensor. In this imaging system, the sensor is driven by the FPGA, the differential data output by the sensor is decoded by the FPGA, and a series of image processing algorithms are implemented in the hardware description language through FPGA programming to improve the imaging quality of the system at night. The main problems solved by this imaging system are as follows: (1) For night time light energy is weak, and after adding an IR cut filter, the sensor can capture the problem of insufficient light. This paper proposes an imaging method without an IR cut filter. This method requires a color correction algorithm in the FPGA to correct the color distortion caused by the transmission of near-infrared light. (2) The problem of low contrast and insufficient color saturation for night time imaging results. This paper combines the gamma correction algorithm and the defogging algorithm to propose a method that can effectively improve the image color saturation. The combination of the two algorithms can improve the brightness of the nighttime image and make the image more vivid. (3) When imaging a single color sensor at night, the details and brightness of the captured object still do not meet the needs of the human eye. In this paper, a mono and color dual-camera system is used to improve imaging quality. In this system, two sensors are simultaneously imaged, so that the imaging results retain both the color information of the color sensor and the clarity of the mono sensor.
Infrared imaging technology has great applications in various fields of social life, especially in the field of remote sensing. Monitoring the ground through infrared loads on satellites can explore natural resources and improve human production. However, due to limitations of equipment, space and other factors, the cost of performance calibration of space load in space is relatively high. To solve the calibration problem of spectral parameters and imaging parameters of space load in the mid-range infrared range, the parameter calibration technique is studied. The mid-far infrared space load comprehensive performance parameter calibration test system is designed by simulating the space vacuum environment on the ground, and the mid-far infrared space load can be tested in an all-round way before going into the space. The test system consists of a vacuum chamber, an infrared collimation system, a medium-far infrared monochromatic source, a standard surface source differential black body, and a series of standard targets. It can realize comprehensive calibration of spectral parameters and imaging parameters on the same device. The load to be tested is placed in a vacuum chamber to simulate a space vacuum environment. The radiation source is radiated into the vacuum chamber through an optical window to simulate ground radiation, which can achieve relative spectral responsivity, MRTD, NETD, MTF, field of view, and magnification, distortion and other parameters of the test, and achieved good experimental results. The results show that the test system can realize the calibration of the spectral parameters and imaging parameters of the mid-far infrared spatial load.
Computational ghost imaging(CGI), utilizing a single-pixel detector, has been extensively used in many fields. However, in order to achieve a high-quality reconstructed image, a large number of iterations are needed, which limits the flexibility of using CGI in practical situations, especially in the field of object recognition. In this paper, we purpose a method utilizing the feature matching to identify the number objects. In the given system, approximately 90% of accuracy of recognition rates can be achieved, which provides a new idea for the application of single pixel imaging in the field of object recognition
The measurement of the electron multiplying CCD(EMCCD) photoelectric performance parameters plays an important role in the development of the chip and imaging system. Measurement uncertainty is an important index to evaluate the quality of the measurement results. A measurement platform for EMCCD photoelectric performance parameters is set up. An EMCCD camera’s photoelectric performance parameters are measured based on photon transfer technique and the uncertainty of the measurement results is analyzed. Based on the method of GUM, the influences of the integrating sphere light source stability, EMCCD camera electronics system stability, installation posture, stray light in dark environment, camera's digital resolution and measurement sampling on the measurement results are analyzed. Based on the theoretical model of different photoelectric performance parameters, the uncertainty sources are discussed. The combined standard uncertainty is determined by the type A uncertainty and the type B uncertainty. The uncertainty evaluation model is established for the measurement of EMCCD photoelectric performance parameters, including convert gain, readout noise, full well, signal to noise ratio and multiplication gain. The uncertainty of the measurement results is calculated by using the established model. At last, we get the following results: relative standard uncertainty of the convert gain is 0.637% (k = 1), relative standard uncertainty of the readout noise is 0.653% (k = 1), relative standard uncertainty of the full well is 2.384% (k = 1), relative standard uncertainty of the signal to noise ratio is 2.301% (k = 1) and relative standard uncertainty of the multiplication gain is 1.259% (k = 1). The above uncertainty results show that the measurement results of this paper are accurate and reliable.
One fractal interpolation algorithm has been discussed in detail and the statistical self-similarity characteristics of light field have been analized in correlated experiment. For the correlation imaging experiment in condition of low sampling frequent, an image analysis approach based on fractal interpolation algorithm is proposed. This approach aims to improve the resolution of original image which contains a fewer number of pixels and highlight the image contour feature which is fuzzy. By using this method, a new model for the light field has been established. For the case of different moments of the intensity in the receiving plane, the local field division also has been established and then the iterated function system based on the experimental data set can be obtained by choosing the appropriate compression ratio under a scientific error estimate. On the basis of the iterative function, an explicit fractal interpolation function expression is given out in this paper. The simulation results show that the correlation image reconstructed by fractal interpolation has good approximations to the original image. The number of pixels of image after interpolation is significantly increased. This method will effectively solve the difficulty of image pixel deficiency and significantly improved the outline of objects in the image. The rate of deviation as the parameter has been adopted in the paper in order to evaluate objectively the effect of the algorithm. To sum up, fractal interpolation method proposed in this paper not only keeps the overall image but also increases the local information of the original image.
According to the adjustability of the gain multiplier of Electron Multiplying CCD , an image gain adjustment method
based on dynamic gray-level is proposed. Compared to a fixed value adjustment algorithm, the automatic gain
algorithm here is more adaptive,even in low-light conditions , it can achieve better gain values. Experimental results
show that the automatic gain algorithm which combines mean values with the dynamic range of histograms meets the
requirements. Whether it is during the day or at night , the brightness of image can quickly converge to the optimum
range of gray histogram distribution, gray-level dynamic range is also accounted for more than 90% . Judging from the
images obtained: the brightness is moderate, details are clear .
The quantum imaging (ghost) has attracted many attention in recent years. In the ghost imaging scheme, the object
information is captured by the “bucket” detector which has no spatial information. In practical scheme, the CCD array or
the APD are utilized as the “bucket” detector, but the saturation effect of the detector may exist due to the limited
sampling depth of the detector. The two methods are presented to reduce the effect of the saturation for different “bucket”
detectors. The method for CCD array is based on the statistic principle of ghost imaging, and the other is based on the
compressed sensing. After that, we compare the difference between the ghost imaging and compressed sensing in the low
light level condition.
Electron Multiplication Charge Couple Device (EMCCD) has an outstanding performance in the low-light imaging field for its high sensitivity, high quantum efficiency, and low noise characteristics. Generally we obtain clear low-light images by increasing the multiplication gain of EMCCD. However, with the gain improved the noise will increase rapidly at the same moment, which makes a big influence on EMCCD imaging quality. At present the noise parameter estimation algorithms of EMCCD mainly have maximum likelihood estimation method and expectation maximization estimation method, etc. These algorithms are complicated and the requirement for initial value is high which make them more difficult to achieve. On the other hand, the moment estimation method applied in this paper has a lower complexity and a wider application. So in this paper we have made a study of the particularity and complexity of EMCCD noise distribution model and then established a suitable noise distribution model for image processing. We calculated the EMCCD noise parameter estimation by using the moment estimation method, and obtained a higher accuracy of noise parameter estimates. Then we used the wavelet semi-soft threshold algorithm into EMCCD image noise filtering processing while the image was added the mixed Poisson-Gaussian noise generated by the simulation of moment estimation. At the end, the simulation results show that the algorithm we used can filter out noise effectively, restore clear images, and can retain details and edge information of image at the same time.
Traditional median filtering algorithm is mainly designed for stationary noise density, which realizes the image smooth but leads to edge fuzzy. The noise density of Electron Multiplying CCD (EMCCD) image varies with the gain. In this paper, a new noise detection and fuzzy adaptive median filter (NDFAMF) is proposed to overcome such drawbacks. First, the noise pixels in the center of the filter window were identified. Secondly, the thresholds were introduced for the detected “noise points”. Based on the thresholds and median of the filtering window, the fuzzy membership function of noise points was put forward, using the fuzzy membership function to filter the noise points. Finally, according to the density of noise in the filtering window the filtering window can change the size adaptive. Simulation and experimental results show that the new algorithm is able to remove noise pixels effectively and protect the details well in the image. The performance is better than the other median filters under the condition of low noise density and relatively stable under the condition of high noise density.
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