Correlated Percolation, Fractal Structures, and Scale-Invariant Distribution of Clusters in Natural Images

自然图像中聚类的相关渗流、分形结构和尺度不变分布

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Abstract

Natural images are scale invariant with structures at all length scales.We formulated a geometric view of scale invariance in natural images using percolation theory, which describes the behavior of connected clusters on graphs.We map images to the percolation model by defining clusters on a binary representation for images. We show that critical percolating structures emerge in natural images and study their scaling properties by identifying fractal dimensions and exponents for the scale-invariant distributions of clusters. This formulation leads to a method for identifying clusters in images from underlying structures as a starting point for image segmentation.

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