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SAR image classification by image intensity similarity and kernel method

机译:基于图像强度相似度和核方法的SAR图像分类

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摘要

Aiming at the classification problem of Synthetic aperture radar (SAR) images, a classifier based on image intensity and structure is constructed. To overcome the disadvantages of conventional template matching algorithms, similarity between two images is calculated by Hausdorff function, which can handle the distortions and pixel perturbations. The function is then fed into Support vector machines to eventually accomplish the task of image classification. Experiment results corresponding to field and simulated data show that this method characterizes target structure information well.
机译:针对合成孔径雷达图像的分类问题,构造了一种基于图像强度和结构的分类器。为了克服传统模板匹配算法的弊端,通过Hausdorff函数计算两幅图像之间的相似度,该相似度可以处理失真和像素扰动。然后将该功能输入支持向量机,以最终完成图像分类任务。与现场和模拟数据对应的实验结果表明,该方法能够很好地表征目标结构信息。

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