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MAXIMUM A POSTERIORI-BASED AUTOMATIC TARGET DETECTION IN SAR IMAGES

机译:SAR图像中基于后验的最大自动目标检测

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摘要

The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.
机译:提出了一种基于最大后验概率(MAP)的合成孔径雷达(SAR)图像自动目标检测算法。该算法分为三个步骤。首先,它采用高斯混合分布来近似和估计SAR图像的多峰直方图。然后,基于MAP的原理,当先验概率既未知又未知时,则将样本像素分为不同的类别c = {target,shadow,background}。最后,它比较了两种不同目标检测的结果。仿真结果优选地表明,所提出的算法是快速且鲁棒的,具有所获先验概率,目标检测的方法是可靠且有希望的。

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