Textures vs Non-Textures: A Simple Computational Method for Classifying Perceived ‘Texturality’ in Natural Images

Abstract

The visual system represents textural image regions as simple statistics that are useful for the rapid perception of scenes and surfaces. What images ‘textures’ are, however, has so far mostly been subjectively defined. The present study investigated the empirical conditions under which natural images are processed as texture. We first show that ‘texturality’ – i.e., whether or not an image is perceived as a texture – is strongly correlated with the perceived similarity between an original image and its Portilla-Simoncelli (PS) synthesized image. We found that both judgments are highly correlated with specific PS statistics of the image. We also demonstrate that a discriminant model based on a small set of image statistics could discriminate whether a given image was perceived as a texture with over 90% accuracy. The results provide a method to determine whether a given image region is represented statistically by the human visual system.