Image representational model for predicting visual distinctness of objects

We show that a notion of congruence in statistical structure across 2D frequency bands produces a useful definition of visual patterns for perceiving target distinctness. In order to reach such a conclusion, firstly, the notion of congruence is used to induce a representational model for 2D images. Secondly, the visual-pattern based representational model is used to define a visual target distinctness metric that involves applying a simple decision rule over the distances between the visual patterns. Finally, a relation is established between the computational distinctness metric and psychophysical target distinctness estimates.