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 针对已有方法对图像逐像素进行分析的不足,将人眼的注意力选择计算模型引入到遥感图像的机场目标检测中,提出一种基于图像显著性区域的遥感图像中机场目标检测与识别的方法,以提高自动目标检测的效率.首先利用霍夫变换对遥感图像中是否存在机场目标进行初步筛选,然后利用改进后的基于图像的视觉显著性模型提取显著性区域,根据区域上的尺度不变特征变换特征并结合多层分类回归树完成机场目标的识别.实验结果表明,该方法比现有的其他机场检测方法具有速度快、识别率高、虚警率低的特点,同时对噪声有较强的鲁棒性. 更多还原

【Abstract】 In this paper we propose a new airport detection and recognition method for remote sensing images based on salient areas with the introduction of visual attention models to improve the efficiency of automatic target detection.Firstly,Hough transform is used to judge the existence of an airport,and then the improved graph-based visual saliency(GBVS) model is used to extract regions of candidates(ROCs).According to the features with scale-invariant feature transform(SIFT),which are extracted from ... 更多还原