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Aircraft Target Detection in Polsar Image based on Region Segmentation and Multi-Feature Decision

机译:基于区域分割和多特征决策的POLSAR图像中的飞机目标检测

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This paper presents a novel aircraft target detection method based on the combination of region segmentation and multi-feature decision. First, the maximum entropy threshold is used to segment region of interest (ROI) like runway, apron and related regions from PolSAR image. Then suspected aircraft targets are extracted in ROI with the feature of dissimilation scattering power. Polarimetric scattering properties of targets and their environmental information are used to construct a detection feature for true aircraft decision from the suspected ones. Experimental results with measured data show that the algorithm can effectively detect aircraft targets with less false and missing alarm rates.
机译:本文提出了一种基于区域分割和多特征决策的组合的新型飞机目标检测方法。首先,最大熵阈值用于从Polsar图像的跑道,围裙和相关区域等感兴趣区域(ROI)。然后在ROI中提取疑似飞机靶标,具有异化散射功率的特征。目标和环境信息的偏振散射特性用于构建来自疑似飞机的真正飞机决定的检测特征。测量数据的实验结果表明,该算法可以有效地检测具有较少虚假和缺失的报警速率的飞机目标。

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