Dead leaves and the dirty ground: low-level image statistics in transmissive and occlusive imaging environments

Abstract

The opacity of typical objects in the world results in occlusion, an important property of natural scenes that makes inference of the full three-dimensional structure of the world challenging. The relationship between occlusion and low-level image statistics has been hotly debated in the literature, and extensive simulations have been used to determine whether occlusion is responsible for the ubiquitously observed power-law power spectra of natural images. To deepen our understanding of this problem, we have analytically computed the two- and four-point functions of a generalized "dead leaves" model of natural images with parameterized object transparency. Surprisingly, transparency alters these functions only by a multiplicative constant, so long as object diameters follow a power-law distribution. For other object size distributions, transparency more substantially affects the low-level image statistics. We propose that the universality of power-law power spectra for both natural scenes and radiological medical images, formed by the transmission of x-rays through partially transparent tissue, stems from power-law object size distributions, independent of object opacity.