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Sequential Discrimination with Multi-Features to Remove False ROIs in SAR ATR

机译:具有多项功能的顺序区分以消除SAR ATR中的错误ROI

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Because the prescreening usually adopts an anomaly detection approach to highlight the vehicle-targets in SAR image, many false regions of interest (ROIs) are produced to reduce hardly the efficiency of the ATR. A new method based on sequential discrimination with multi-features is proposed to remove these false ROIs in this paper. By quantitatively analyzing the redundancy, robustness and separability of the candidates, the optimal features are selected to form an orderly vector, which is compared with the vector of threshold to finish a sequential discrimination. The performance of the above algorithm is validated by the X band MSTAR data, and is compared with the quadratic distance discriminating (QDD) method.
机译:由于预筛选通常采用异常检测方法来突出SAR图像中的车辆目标,因此会产生许多错误的感兴趣区域(ROI),从而几乎不会降低ATR的效率。提出了一种基于序贯特征的多特征消除新方法。通过定量分析候选的冗余度,鲁棒性和可分离性,选择最佳特征以形成有序向量,将其与阈值向量进行比较以完成顺序判别。通过X波段MSTAR数据验证了上述算法的性能,并将其与二次距离判别(QDD)方法进行了比较。

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