Orbit target IR characteristic is the basis of the IR imaging detection equipment design, the corresponding digital simulation model validation, and the application processing development, such as the target detection and tracking. In the work, an infrared measurement system for simulated space target is represented. The system can acquire the infrared characteristics of the target in the simulated space environment on the ground. In order to simulate the whole orbit environment, vacuum chamber and solar simulator are used in the work. An IR window is developed for the system. Then measurement instruments can be place outside the chamber to get the characteristic through the IR window. The work also provides a method to calibrate the IR window. The IR characteristic at the wavelength range of 3 μ~12 μm can be obtained with the system.
The marine and air background images obtained by a single shipborne infrared sensor often have problems such as low contrast between target and background, high noise, and lack of complete target details, which bring great difficulty to the extraction of ship targets. This paper analyzes the basic features of the ship target in medium/long wave infrared image and proposes the basic model of ship target extraction based on the Markov Random Field (MRF) theory. According to the two-band target and background prior probability distribution, the energy minimization framework is added. Regional believable propagation (BP) algorithm is used to perform global optimization of the model, and image segmentation label is estimated according to MAP criteria. The experimental results show that the fusion extraction algorithm can retain the effective components in the original dual-band infrared image, and the extraction efficiency and accuracy are higher.
In order to detect satellite under sky background, we propose an optimized satellite object detection extraction and tracking algorithm under the sky background. The proposed satellite tracking processing consists of two stages. In the first stage of object detection and extraction, the background template based on the mixture Gaussian model is used to establish background frame, and then the background is removed by inter-frame difference method to obtain the object. In the subsequent object tracking stage, this paper proposes an improved untracked Kalman filter algorithm for object tracking. Firstly, it tracks multiple suspected objects in the background, and then introduces a path coherence function to eliminate the false objects. Compared with other methods, the experimental results show that our method can better meet the real-time requirement, eliminate false objects appeared in the sequence of images more efficiently and make the tracking trajectory smoother.
Orbit target IR model can be used to design orbit target detection sensor, generating simulation data to validate the data processing algorithms, such as the target detection and tracking. In the work, a novel orbit target IR model is built. IR detection uses the difference between the target and the background to achieve the target effectually. In order to increase the application ability, the IR model consists of the orbit target and the celestial background. The geometry module and IR radiometric module make up the orbit target IR model. The professional geometry modeling software CAD is used to build the geometry model. The reflection between the subassembly is considered in the radiometric, because the thermal control coat of the satellite (such as optical solar reflector) has very high specular reflectance generally. The Midcourse Space Experiment (MSX) catalog is used to calculate the IR celestial IR background. The IR radiation provided by the MSX is used to calculate the equivalent temperature and the observation angle by the SPSO (Stochastic Particle Swarm Optimization) method. The transfer algorithm adopted in this paper is compared with the Monte-Carlo method, and the results show that the relative deviation between them is less than 10%.
With the rapid development of China's space industry, digitization and intelligent is the tendency of the future. This report is present a foundation research about guidance system which based on the HSV color space. With the help of these research which will help to design the automatic navigation and parking system for the frock transport car and the infrared lamp homogeneity intelligent test equipment. <p> </p>The drive mode, steer mode as well as the navigation method was selected. In consideration of the practicability, it was determined to use the front-wheel-steering chassis. The steering mechanism was controlled by the stepping motors, and it is guided by Machine Vision. The optimization and calibration of the steering mechanism was made. A mathematical model was built and the objective functions was constructed for the steering mechanism. <p> </p>The extraction method of the steering line was studied and the motion controller was designed and optimized. The theory of HSV, RGB color space and analysis of the testing result will be discussed <p> </p>Using the function library OPENCV on the Linux system to fulfill the camera calibration. Based on the HSV color space to design the guidance algorithm.
FOV separation (between VNIR sensor and SWIR sensor) and motion compensation imaging modes are introduced into the pushbroom imaging spectrometer to increase the SNR of the imaging data sometimes. Besides the higher SNR, the two imaging modes result in some bad effects on the imaging data, such as the additional misregistration. In the paper, a digital simulator for pushbroom Offner hyperspectral imaging spectrometer is used to analyze the misregistration caused by the FOV separation and the motion compensation imaging modes. Based on the imaging process, the simulator consists of a spatial response module, a spectral response module, and a radiometric response module. The FOV separation is simulated in the imaging position calculation process of the spatial response module, and the motion compensation is considered in both the imaging position simulation and the radiometric response module. Using the simulator, the imaging position data is created to quantify the misregistration. The result shows that the imaging track deviation, caused by the FOV separation, between the VNIR sensor and SWIR sensor keeps a constant quantity in the latitude direction. However, the deviation will increase along with the imaging time in the longitude direction. When the two imaging modes are both considered, the deviation is symmetrical relative to the nadir point in the latitude direction. However, the deviation is not symmetrical in the longitude. In order to analyze the misregistration effect on the imaging data, simulation data with different imaging modes on Dongtianshan remote sensing testing field is created using the simulator. And the misregistration effect on the spectra of flat ground pixel and rugged ground pixel are analyzed.
For two participants to compare the equality of their private information without revealing them, a new quantum private protocol with the help of semi-honest third party TP is proposed. Different from previous protocols, the four particle |<i>W<sub>f</sub></i>⟩ state and the |<i>χ</i><sup>+</sup>⟩ state are utilized in this protocol as the carriers of quantum information and form the entanglement swapping as basic principle. The simple measurement of quantum states and exclusive-or operation are only required to conduct in this protocol. What’s more, this protocol can compare two bits of two participants’ private information in every comparison time. Meanwhile, it needs no unitary operation to fulfill this protocol. This protocol is feasible and efficient to execute through these aspects. In the end, the security of this protocol is analyzed at great length from two kinds of attacks including the outside attack and the participant attack. And the analysis result shows that this protocol can withstand various kinds of attacks and be secure to perform efficiently.
Restoring blurred image，as one of the hot issues in the field of image processing，has important significance in improving the image quality. In recent years, a variety of methods for removing motion blur of an image have been proposed, but most of the algorithms are too complex and not applied. This paper educes an efficient algorithm for motion-blurred image. According the temporal profile of the infrared detector, point spread function (PFS) of the uniform linear motion-blurred image is discussed. The profile of the PSF is acquired by iterative Weiner-filter. Experimental results show that the method has accurate and applied performance for infrared blurred image got from actual system.
The adaptive optical telescopes play a more and more important role in the detection system on the ground, and the adaptive optical images are so many that we need find a suitable method of quality evaluation to choose good quality images automatically in order to save human power. It is well known that the adaptive optical images are no-reference images. In this paper, a new logarithmic evaluation method based on the use of the discrete cosine transform(DCT) and Rényi entropy for the adaptive optical images is proposed. Through the DCT using one or two dimension window, the statistical property of Rényi entropy for images is studied. The different directional Rényi entropy maps of an input image containing different information content are obtained. The mean values of different directional Rényi entropy maps are calculated. For image quality evaluation, the different directional Rényi entropy and its standard deviation corresponding to region of interest is selected as an indicator for the anisotropy of the images. The standard deviation of different directional Rényi entropy is obtained as the quality evaluation value for adaptive optical image. Experimental results show the proposed method that the sorting quality matches well with the visual inspection.