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首页> 外文期刊>Aerospace and Electronic Systems Magazine, IEEE >Morphology-based building target detection from forward-looking infrared imagery in dense urban areas
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Morphology-based building target detection from forward-looking infrared imagery in dense urban areas

机译：在人口稠密的市区中通过基于形态学的建筑目标检测前瞻性红外图像

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摘要

In this article, we have presented a morphology-based method for building recognition from FLIR image sequences captured by the midwave calibrated camera in dense urban areas. Based on the imaging parameters (the horizontal and vertical angle of field of view, the imaging distance, and the elevation), the imaging size of the building target can be determined in real time, and then the SE, which has a high correlation with the target's imaging size, has been generated. Additionally, to improve the performance of target detection and straight-line extraction, the line segment grouping method and the gradient-based straight-line extraction method are adopted. Experimental results show the algorithm can recognize the prominent building object with higher local contrast in FLIR image sequences in dense urban areas and maintain higher performance.
机译：在本文中，我们介绍了一种基于形态学的方法，用于从密集城市地区的中波校准相机捕获的FLIR图像序列中进行建筑物识别。根据成像参数（水平和垂直视场角，成像距离和高程），可以实时确定建筑物目标的成像尺寸，然后确定SE，与目标的成像尺寸已生成。另外，为了提高目标检测和直线提取的性能，采用了线段分组方法和基于梯度的直线提取方法。实验结果表明，该算法能够识别稠密城市地区FLIR图像序列中具有较高局部对比度的突出建筑对象，并保持较高的性能。

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