Efficient coding of natural scene statistics predicts discrimination thresholds for grayscale textures.

ABSTRACT: Previously, in Hermundstad et al., 2014, we showed that when sampling is limiting, the efficient coding principle leads to a 'variance is salience' hypothesis, and that this hypothesis accounts for visual sensitivity to binary image statistics. Here, using extensive new psychophysical data and image analysis, we show that this hypothesis accounts for visual sensitivity to a large set of grayscale image statistics at a striking level of detail, and also identify the limits of the prediction. We define a 66-dimensional space of local grayscale light-intensity correlations, and measure the relevance of each direction to natural scenes. The 'variance is salience' hypothesis predicts that two-point correlations are most salient, and predicts their relative salience. We tested these predictions

SUBMITTER: Tesileanu T 

PROVIDER: S-EPMC7494356 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature