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SAR Image Retrieval Based on Gaussian Mixture Model Classification

机译:基于高斯混合模型分类的SAR图像检索

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SAR image retrieval,lacking of well performance recently due to the particularity of SAR image,has drawn more and more attention with the increasing volume of SAR data and the dramatically enlarging application range of SAR image. This paper considers both the characteristic of content-based image retrieval (CB1R) and SAR image,proposing a novel SAR image retrieval method. The proposed method can be divided into two parts:image classification and matching.Firstly we use Gaussian Mixture Model (GMM) to gain a precise result of classification,and then we get the retrieval results through the integrated region matching (IRM) algorithm.Experimental results show that the proposed method can retrieve SAR images which contain all kinds of surface features effectively.
机译:SAR图像检索由于其特殊性而近来缺乏良好的性能,随着SAR数据量的增加和SAR图像的应用范围的急剧扩大,受到越来越多的关注。本文考虑了基于内容的图像检索(CB1R)和SAR图像的特点,提出了一种新颖的SAR图像检索方法。所提出的方法可以分为两部分:图像分类和匹配。首先使用高斯混合模型(GMM)获得精确的分类结果,然后通过综合区域匹配(IRM)算法得到检索结果。结果表明,该方法能够有效地提取出包含各种表面特征的SAR图像。

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