Saremi Saeed, Sejnowski Terrence J
IEEE Trans Pattern Anal Mach Intell. 2016 May;38(5):1016-20. doi: 10.1109/TPAMI.2015.2481402. Epub 2015 Sep 23.
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.
自然图像在所有长度尺度上的结构都是尺度不变的。我们利用渗流理论构建了自然图像中尺度不变性的几何观点，该理论描述了图上连通簇的行为。我们通过为图像的二值表示定义簇，将图像映射到渗流模型。我们表明，临界渗流结构出现在自然图像中，并通过识别簇的尺度不变分布的分形维数和指数来研究它们的标度性质。这种表述导致了一种从底层结构识别图像中簇的方法，作为图像分割的起点。
