CAJ | 학술논문

针对星载光学遥感图像城市街区复杂背景问题，提出一种车辆目标自动检测方法。首先，利用场景中植被背景的物理属性，通过多光谱波段抑制场景中的植被背景，然后，在分析城市街区地物形态反射率特性的基础上，利用全色波段并结合二值形态学方法抑制场景中的建筑物，最后，引入著名的RX算法对抑制后的图像进行车辆目标检测。将文中提出的方法应用于实际Quickbird影像的车辆目标检测，结果表明所提出的方法具有鲁棒性强，执行效率高，不需要人工辅助等方面的特点，可用于城市街区车辆目标的自动检测。
침대성재광학요감도상성시가구복잡배경문제，제출일충차량목표자동검측방법。수선，이용장경중식피배경적물리속성，통과다광보파단억제장경중적식피배경，연후，재분석성시가구지물형태반사솔특성적기출상，이용전색파단병결합이치형태학방법억제장경중적건축물，최후，인입저명적RX산법대억제후적도상진행차량목표검측。장문중제출적방법응용우실제Quickbird영상적차량목표검측，결과표명소제출적방법구유로봉성강，집행효솔고，불수요인공보조등방면적특점，가용우성시가구차량목표적자동검측。
It is difficult to detect vehicles in city area by using paceborne optical remote sensing images, because the background in city area is too complex. In this paper, an automatic vehicle detection method was proposed to address the issue by using background segmentation method. Firstly, the physical property of the vegetation was analyzed and used to suppress the vegetation background of a scene by using the multi- spectral information of the scene. Next, the reflectance characteristics of city area cover types were analyzed. Based on the reflectance characteristics of building roofs and roads, the building background in the scene was removed by employing the binary morphological method on the panchromatic band image. Finally, the famous RX algorithm was introduced to detect the vehicles on the vegetation and building background suppressed image. The proposed method is applied to the actual Quickbird image for vehicle target detection. The results show that the proposed method has strong robustness, high efficiency, and automatic characteristics, and can be used for vehicle detection in city area.