To realize the quantitative measurement on infrared radiation of space objects, astronomical calibration of star radiation measurement system needs to be addressed. Considering the deficiencies of traditional ground-based large-aperture infrared radiation measurement systems in star calibration, we proposed a novel infrared radiation measurement system which contains four parts: the star observation unit, the infrared star measurement unit, the information processing unit, and the computing unit. Through optimal design of the radiation measurement system, we achieve effective distinction of target and complex backgrounds, and precise calculation of target infrared radiation.
Abstract Space debris detection is important for space asset protection and space situational awareness. The current environment of man-made satellites and space debris objects in Earth orbits increases rapidly, so does the probability of collision between them. In this paper, we propose a space debris detection method based on image alignment and connected region analysis. First, the median filter and an improved top-hat filter are used for pre-process of the original images, which can eliminate thermal noises and improve optical distribution integrity of targets. Second, a feasible and easy-to-implement connected region labeling method is used for centroid extraction of suspected targets. Meanwhile, several saliency features of targets are used for suspected targets confirmation and false alarms elimination. Then, we use stars in high-brightness magnitude as feature points for accurate interframe registration, which can suppress the influence of platform shaking and background movement on dim target trajectory associations. Finally, data association is used for target trajectory extraction. The experiment is performed using one astronomical image sequence, the results show that the proposed method is robust and efficient on complex backgrounds.
To detect dim small target in infrared images, considering the target velocity and intensity characteristics we proposed a new spatial and temporal method. The new spatial and temporal method consists of a 2D spatial model and a 3D spatial and temporal model. The 2D spatial model is utilized to pre-process of the original infrared images. The 3D spatial and temporal model is used to enhance the probable targets by estimating the direction of the target and accumulating the grayscale to the central pixel. Experiments show that our method gains better detection performance in infrared videos with the complex background.
Small target detection in wide-area surveillance is a challenging task. Current imaging staring sensors in practical systems are characterized by large pixel counts and wide field of view (WFOV). Therefore, it is not suitable to detect targets simply via a single algorithm in different background types. We solve this problem by local windowing approach and take different background suppression and target enhancement methods for different surveillance scenarios. Monte Carlo simulations are provided and the experimental results demonstrate that we can effectively detect dim small targets with a very low false alarm rate and an acceptable detection rate in the proposed detection architecture.
In order to detect the dim small target in high frame rate image sequences,an optimized temporal processing technique is
investigated. Based on the temporal profile models for noise pixel,target pixel and clutter pixel, we formulate the
detection in two steps, pre-processed by Max-median filter and temporal variance filter(TVF). In pre-processing step,
three spatial-filtering methods are compared. In temporal profile analysis step, the length of time windows for calculating
the mean and variance values are chosen after statistical analysis. Finally, six targets embedded into a scene which
contains different types of clouds, and set the adjacent scene to one pixel jitter in any random direction. The simulation
results show that we can obtain a relative high signal-to-clutter gain in different regions, which satisfies the requirement
of target detection algorithm in high frame rate detection system.
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