Information communication ability is very important in the airport terminal area, especially for the commander, who needs to grasp and analyse a large number of data to make the accurate command decision in real time. Aiming at this problem, this paper introduces the visualization decision-making system of airport terminal area, which changes the input and output flow of a large number of data and graphs in the past evaluation system, and integrates a great deal of technical work such as organization planning, implementation and efficiency evaluation of air communication in the background. The visual graphical interface provides a convenient situation analysis and assistant decision-making tool for the commander. The system realizes the communication planning and coordination matching with the mission, the information identification and fusion corresponding to the flight dynamics, the analysis and application of the interference response, and the data analysis and evaluation of the post-mission summary support.
Color constancy is of important for many computer vision applications, such as image classification, color object recognition, object tracking and so on. But unlike the human visual system, imaging device cannot be able to compute color constant descriptors which do not vary with the color of the illuminant, so solving color constancy problem is necessary. In the calculation of color constancy, illuminant estimation is the key. Because grey surfaces can perfectly reflect the color of the scene illumination, many methods have been proposed to identify grey surfaces to estimate the illuminant. But they either rely on the camera’s parameters, lacking universality, or work inaccurate in worse conditions. In order to solve these problems, in this paper, an iterative method is proposed. The quality of the proposed method is tested and compared to the previous color constancy methods on the Macbeth Chart and two data sets of synthetic and real images. Through MATLAB simulation, experimental pictures and quantitative data for performance evaluation were gotten. The simulated results show that the proposed algorithm is accurate and efficient in identification of the grey surfaces, even in worse condition. And it performs well in color constancy computation on both synthetic and real images.
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