Deblurring turbulent images is an active topic in image processing and low-level vision research. Existing methods usually use the parametric physical model for nonblind image restoration, which lacks adaptability to different turbulent scenes. To overcome this challenge, a dual patch-wise pixels (DPP) prior is proposed for effective blind deblurring of turbulent images. A DPP-based turbulent image deblurring model was established based on the fact that the value of the DPP decreases through the turbulent blurring process, which has been proven both mathematically and experimentally. To solve the nonlinear DPP in the model, a linear mapping operator was constructed. Additionally, half-quadratic splitting and threshold methods were used to solve the L0 regularization term. Experimental results showed that the proposed algorithm performs well on various types of turbulent scenes as well as real images and outperforms state-of-the-art algorithms in terms of computational efficiency and effectiveness.
Space-based infrared detection, which plays an important role in both national safety and people's daily life, is an essential means of aerial surveillance. However, the traditional performance characterization method used in the current system is difficult to distinguish aerial targets from complex backgrounds effectively, which is mainly manifested as low signal-to-clutter ratio (SCR). In this paper, a novel characterization method based on infrared differential analytic factor (IDAF) is proposed to characterize the radiation difference between the target and complex background and select the detection bands. The simulation experiment shows that the modified SCR improves over three orders of magnitude compared with the traditional performance characterization methods under different backgrounds.
KEYWORDS: Visualization, Infrared radiation, Target recognition, Signal to noise ratio, Signal processing, Target detection, Data modeling, Interference (communication)
Infrared target recognition is an important task in space-situational awareness. In the space target detection process, due to the small energy of the point target, it is easy to make the target disappear from the detection field of view under the interference of dense noise, resulting in a decline in recognition system performance. Reasonable representation of the infrared characteristics of a target is an effective means of improving the stability of recognition systems. In this study, a one-dimensional radiation intensity sequence was mapped to a two-dimensional space based on the Gramian angle field, Markov transition field, and recurrence plots to visualize the structural mode of the target radiation intensity sequence and the dynamic properties of the system generating the sequence. On this basis, a recognition framework based on convolutional neural networks was proposed to train and recognize three types of visualized signals and raw data. The experimental results showed that the proposed recognition method based on visualized signals can effectively identify the target and is robust against noise interference and missing data.
Flexible thermal strap is a key component for space optical system to realize cold transfer, insulate vibration. The thermal link based on high thermal conductivity graphene film becomes a hot spot for this application. In order to reduce the loss in the heat transfer process, a study on the heat transfer performance and structural form of the thermal link made by pyrolytic graphite films (PGF) is carried out, the thermal resistance network model of the thermal strap is analyzed, the relationship between the heat transfer, the heat transfer temperature difference at the mounting surface and the number of graphite film layers is established by combining theoretical analysis and DOE design methods. A method for quickly determining the design parameters of the thermal strap is proposed. The PGF thermal strap designed according to this method achieves a small temperature difference which less than 1.7K between the cold tip and the simulated optical bench coupling surface, a length of 117mm for the strap, and a weight of only 60g, when it used to transfer 5W cooling capacity at 200K.
Using the observation data of various detectors to identify reentry vehicles, heavy and light decoys, and separate debris is a key task in space situational awareness. During the flight, the space targets are always in a rotating or rolling state (called micromotion). micromotion can reflect the physical attribute information such as mass distribution and shape of different targets, which provides important essential characteristics for identifying space targets. Infrared sensor has the advantages of working all day, long detection distance, and small load. The image data obtained by it can be used to estimate the temperature, radiation, and other information, but the research on estimating the target micromotion characteristics from the multi-infrared images is rarely mentioned. Therefore, aiming to solve the problem of micromotion period estimation of space infrared moving targets under long-distance observation, firstly, considering the factors such as flight scene, target shape and micromotion, the infrared radiation and imaging models of space moving targets under micromotion state are established according to the micromotion dynamics, temperature and imaging relationship; Secondly, the period of infrared radiation extracted from multi-frame images is estimated. Through theoretical analysis, it is pointed that the assumption that there must be a similarity between the sample sets sampled by period length is the main reason for the doubling misjudgment of the average amplitude difference (AMDF) function, and there is also a false valley misjudgment problem in AMDF. The cyclic average amplitude difference function (CAMDF) is used to estimate the micromotion period of multi-shape objects, which can not only effectively decrease the double misjudgment of the period but also solve the misjudgment of false valley estimation points. Finally, a semi-physical simulation platform for space infrared dim moving target detection and recognition is designed and built, and the experimental data is used to verify the effectiveness of CAMDF in estimating the micromotion period. The results show that when the signal-to-noise ratio(SNR) of the simulated infrared radiation is greater than 15, the average accuracy of CAMDF is greater than 90%; Experimental data of five shape objects is used to verify the algorithm, and the average relative error is about 6%. It shows that the algorithm can better estimate the micromotion period of space targets.
In the process of point target detection, the blind pixel can easily lead to wrong detection of point target. Aiming at the defect that the conventional blind pixel detection method cannot detect the random blind pixel dynamically, a blind pixel dynamic detection method for IRFPA towards point target was proposed. In this method, the suspicious point targets which are removed by the multi-frame detection of point targets are chosen as potential blind pixels. Blind pixel feature model is used to match potential blind pixels, and the likelihood function of the confirmed blind pixel is characterized by multi-frame accumulation. In the subsequent detection, the blind pixels are dynamically detected by using the blind pixel likelihood function which is iteratively updated by the detection result, so as to adaptively detect blind pixel. The results showed that this method can dynamically eliminate random blind pixel and fixed blind pixel without interrupting the detection process of the point target, and at the same time improve the detection accuracy of the point target with a small amount of computation and is easy to be implemented by hardware.
Targets detection in single band images has problems such as poor clutter suppression capability and high false alarm rate, while the difference in imaging characteristics of the aerial target between the mid-length wave and the long-length wave is obvious and complementary, so dual-bands fusion can be utilized to improve detection efficiency and performance. An rapid infrared dual-band fusion target detection method based on local contrast method (LCM) is proposed, searching targets rapidly and extracting targets features in the mid-length wave images from same scene, finally fusing two bands images for precise positioning. The multi-scales LCM is used to quickly perform full-image range background suppression and target enhancement in lower-resolution long-length wave images, then the suspicious target position is obtained and sliced. Following the guidance from the long-length wave images, the position of targets is extracted at the corresponding position in the higher-resolution mid-length wave image. Two positions from different resolution images are fused, and the target is accurately positioned. This method achieves rapid detection of aerial targets in infrared images effectively, which has certain engineering application value.
KEYWORDS: Temperature metrology, Monte Carlo methods, Target detection, Infrared radiation, Solar radiation, Computer simulations, Solar radiation models, Error analysis
When the target to be measured temperature is far away, and the prior information of the target such as the emissivity of the detected object can not be known, the traditional infrared single-band temperature measurement method will produce larger temperature measurement error. According to the characteristics of target infrared radiation spectrum, assuming that the target is grey body, this paper uses infrared dual-band temperature measurement algorithm and Monte Carlo method to extract the temperature feature of the object under test. The effectiveness of the algorithm is analyzed. The influence of parameters such as iteration times of the algorithm and the minimum error threshold of dual-band radiation ratio on the accuracy of target temperature inversion is simulated and analyzed. On this basis, the influence of different target emissivity, distance between wavebands and detection distance on target temperature inversion accuracy is analyzed. The results show that the two-band temperature measurement algorithm can extract the target temperature information quickly and accurately under the set parameters, and the temperature inversion error is related to the distance between infrared bands. This provides guidance for improving the accuracy of target temperature measurement in practical measurement.
With the continuous occurrence of aircraft crash, it is very important to realize the detection of aerial targets on the spaced-based platform. Many countries have carried out some researches in this field, but there is still no good conclusion about the methods and systems for aerial target detection. Meanwhile, the actual cost of satellite experiments is very expensive, and it is impractical to test the detection system by launching satellites several times. Therefore, the system simulation model can be used as the basis for the design of detection system. In the simulation process, combined with the optical system parameters and detector indicators, the imaging relationship between the satellite platform, the turntable and the target are calculated, and various imaging modes such as scanning and gazing are obtained according to the specific parameters of the actual application. This simulation mode directly presents the actual satellite motion, camera imaging and target motion state. And such a simulation system greatly shortens the actual design time of the system in engineering applications. It more realistically inverts the actual operating state and can obtain the detection result without the actual satellite launch. And such a simulation system can flexibly change parameters according to the actual conditions, so it can not only be applied to aerial targets detection, but also play an important role in other fields.
Soil moisture (SM) is a key variable in controlling the water, carbon, and energy exchange processes of land atmosphere interface. One of the widely used approaches to retrieve soil moisture is based on satellite remote sensing technology. However, these spatiotemporally continuous soil moisture products retrieved from microwave remote sensing data are not able to meet the accuracy requirement of flood prediction and irrigation management due to the coarse spatial resolution. As one of the relatively new passive microwave products, The Fengyun-3B Microwave Radiation Imager (FY-3B/MWRI) soil moisture product was retrieved from passive microwave brightness temperature data based on the Qp model. However, it has rarely been applied at the catchment and regional scale due to the coarse resolution with 25- km grid. In this study, the Fengyun-3B soil moisture product was downscaled from 25-km to 1-km based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. The downscaling approach uses MODIS land surface temperature (LST) and normalized difference vegetation index (NDVI) to construct soil evaporative efficiency (SEE). The 1-km SM was then estimated based on the difference value of high resolution and average SEE in original FY3B pixel. The downscaling method was applied to every Fengyun-3B pixel in the Naqu area on the Tibetan Plateau to retrieve the downscaled 1-km resolution FY3B soil moisture product. The downscaling results were validated using the in-situ soil moisture from Soil Moisture/ Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in August 2015. The validation results revealed that the downscaling approach showed promising results. We can conclude that the downscaled FY3B SM product better characterize the spatial and temporal continuity and have higher consistency with validation soil moisture data. The approach proposed in this study are applicable to bare surface or sparse vegetation covered land surface.
KEYWORDS: Target detection, Mid-IR, Long wavelength infrared, Infrared radiation, 3D modeling, Optical engineering, Skin, Signal detection, Signal to noise ratio, Infrared detectors
To ensure flight safety of an aerial aircraft and avoid recurrence of aircraft collisions, a method of multi-information fusion is proposed to design the key parameter to realize aircraft target detection on a space-based platform. The key parameters of a detection wave band and spatial resolution using the target-background absolute contrast, target-background relative contrast, and signal-to-clutter ratio were determined. This study also presented the signal-to-interference ratio for analyzing system performance. Key parameters are obtained through the simulation of a specific aircraft. And the simulation results show that the boundary ground sampling distance is 30 and 35 m in the mid- wavelength infrared (MWIR) and long-wavelength infrared (LWIR) bands for most aircraft detection, and the most reasonable detection wavebands is 3.4 to 4.2 μm and 4.35 to 4.5 μm in the MWIR bands, and 9.2 to 9.8 μm in the LWIR bands. We also found that the direction of detection has a great impact on the detection efficiency, especially in MWIR bands.
For the prospects of three-dimensional reconstruction technology based on structure from motion in engineering application, a high-resolution and visible band imaging system has been designed and implemented. It consists of a 5k × 5k CMOS focal plane array detector made by the ON-SEMI company, an optical system and an electronics system designed by ourselves. The electronics system takes FPGA as the control and drive processor chip and is divided into three parts: a power management module, a detector module and an image processing module, capable of finishing image compression and transmission. A sequence of images for the target of long distance away is obtained from the imaging system and the images after cropping and segmentation, aiming at reducing calculation and excluding some points irrelevant with the target during reconstruction process, are took as input of structure from motion. Seeds from the match points expand from sparse points to dense points and the initial model of reconstruction target is achieved. The experiment results show that the imaging system meet the requirement of three-dimensional reconstruction in engineering application and a new novel imaging system design of graded resolution based on bionics is proposed.
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