区域对应的图像匹配通过EMD流

H. Greenspan, G. Dvir, Y. Rubner
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引用次数: 54

摘要

图像的内容可以通过在适当的特征空间中的一组均匀区域来总结。当确切的形状不重要时,区域可以用简单的“blobs”来表示。即使是相似的图像,两个图像中的斑点也可能在形状、位置和所表示的特征上有所不同。此外,一幅图像中的单独斑点可能会在另一幅图像中合并在一起。提出了一种计算两组blob的不相似度的新方法。采用高斯混合建模对输入图像进行表示。利用地球移动距离(EMD)计算图像的不相似性和图像之间的斑点流矩阵。该流用于合并斑点,使图像之间的差异变小。示例显示在合成图像和自然图像上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Region correspondence for image matching via EMD flow
The content of an image can be summarized by a set of homogeneous regions in an appropriate feature space. When exact shape is not important, the regions can be represented by simple "blobs". Even for similar images, the blobs in the two images might vary in shape, position, and the represented features. In addition, separate blobs in one image might get merged together in the other image. We present a novel method to compute the dissimilarity of two sets of blobs. Gaussian mixture modeling is used to represent the input images. The Earth Mover's Distance (EMD) is utilized to compute both the dissimilarity of the images and the flow matrix of the blobs between the images. The flow is used to merge blobs such that the dissimilarity between the images gets smaller. Examples are shown on synthetic and natural images.
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