The Elementary Operations of Human Vision Are Not Reducible to Template-Matching
Fig 1
Same signal but different noise.
Observers were asked to discriminate a vertical Gabor target signal (A) from a non-target signal (blank in F). Four different noise types were added to both target and non-target signals. In the 2D noise condition (B,G) each pixel was assigned a random Gaussian modulation. In the 1D condition (C,H) noise only varied along the horizontal dimension in the form of bar-like Gaussian modulations. In the orientation (Θ) condition (D,I), noise consisted of the sum of a set of Gabor patches spanning the entire orientation range (K), each patch taking on a randomly assigned contrast value (see Methods). Spatial frequency (SF) noise (E,J) was generated using a similar procedure, except the underlying patch set varied across SF (L) rather than orientation. The green (alternatively red) profile in A displays a horizontal (alternatively vertical) slice through the target surface. Green labels in K (alternatively L) point to target location along Θ (alternatively SF) dimensions.