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Research of unsupervised change detection means based on clustering characteristic of 2-D histogram

机译:基于二维直方图聚类特性的无监督变化检测方法研究

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In this paper, a novel image change detection means is proposed based on the clustering characteristic of 2-D histogram. First, the best segmentation direction of 2-D histogram formed by pixel gray levels and the local average gray levels is ascertained by using LSM. Secondly, a kind of new 2-D entropy is defined to search the best threshold line and segment the 2-D histogram into unchanged region and change region. Then the change area in different image is detected based on the change region of 2-D histogram. Finally, the proposed means is compared to traditional means. The theoretical analysis and experiment results confirm the effectiveness of the proposed means.
机译:本文基于二维直方图的聚类特性,提出了一种新颖的图像变化检测方法。首先,通过使用LSM确定由像素灰度级和局部平均灰度级形成的二维直方图的最佳分割方向。其次,定义了一种新的二维熵来搜索最佳阈值线,并将二维直方图分割为不变区域和变化区域。然后,基于二维直方图的变化区域来检测不同图像中的变化区域。最后,将提出的方法与传统方法进行了比较。理论分析和实验结果证实了所提方法的有效性。

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