@article{1fb196e06dc511dd8d9f000ea68e967b,
title = "Natural image profiles are most likely to be step edges",
abstract = "We introduce Geometric Texton Theory (GTT), a theory of categorical visual feature classification that arises through consideration of the metamerism that affects families of co-localised linear receptive-field operators. A refinement of GTT that uses maximum likelihood (ML) to resolve this metamerism is presented. We describe a method for discovering the ML element of a metamery class by analysing a database of natural images. We apply the method to the simplest case––the ML element of a canonical metamery class defined by co-registering the location and orientation of profiles from images, and affinely scaling their intensities so that they have identical responses to 1-D, zeroth- and first-order, derivative of Gaussian operators. We find that a step edge is the ML profile. This result is consistent with our proposed theory of feature classification.",
author = "Griffin, {Lewis D.} and Martin Lillholm and Mads Nielsen",
year = "2004",
doi = "10.1016/j.visres.2003.09.025",
language = "English",
volume = "44",
pages = "407--421",
journal = "Vision Research",
issn = "0042-6989",
publisher = "Pergamon Press",
number = "4",
}