Modeling natural image statistics


This chapter focuses on models of the spatial structure in natural images, that is, the content of static images as opposed to sequences of images. It introduces some statistical qualities of natural images and discusses why it is interesting to model them. The chapter describes several models including the state of the art. It then discusses examples of how natural image models impact computer vision applications. The chapter further describes experimental examples of how biological systems are adapted to natural images. A wide spectrum of approaches to modeling the density of natural images has been proposed in the last two decades. Many have been designed to examine how biological systems adapt to environmental statistics, where the logic is to compare neural response properties to emergent aspects of the models after fitting to natural images.

Matthias Bethge
Matthias Bethge
Professor for Computational Neuroscience and Machine Learning & Director of the Tübingen AI Center

Matthias Bethge is Professor for Computational Neuroscience and Machine Learning at the University of Tübingen and director of the Tübingen AI Center, a joint center between Tübingen University and MPI for Intelligent Systems that is part of the German AI strategy.