Anisotropy in Images Varies with Spatial Frequency and Digital Category: Digital Images Present a Different World to the Viewer

Researchers have described the manner in which the low-level information from images varies with regard to orientation distribution, referred to as the level of anisotropy in an image. Prior work has described deviations from typical real-world (nature, suburban, urban) images in the content of various categories of digital images, including games, social media, and others. The present work extends prior findings by bandpass filtering images across nine categories, analyzing orientation content within each bandpass range and comparing anisotropy across spatial frequency. Anisotropy in this analysis was found to increase with spatial frequency; relatively isotropic orientation information was present in the low bandpass range across all image categories, while medium and high bandpass images show a pattern of increasing anisotropy in a category-dependent manner. In particular, deviations from the distribution defined by nature images characterize multiple categories of digital images; this finding is discussed in terms of potential implications for visual system plasticity and the potential for such changes to impact multiple facets of perception. Potential impacts of this finding on training sets for machine learning tools are also discussed.