A statistical analysis of natural images matches psychophysically derived orientation tuning curves.
A neural net method is used to extract principal components from real-world images. The initial components are a Gaussian followed by horizontal and vertical operators, starting with the first derivative and moving to successively higher orders. Two of the components are 'bar-detectors'. Their measured orientation selectivity is similar to that suggested by Foster & Ward (Proc. R. Soc. Lond. B 243, 75 (1991] to account for brief-exposure psychophysical data. In tests with noise images, the ratio of sensitivity between the two components is controlled by the degree of anisotropy in the image.
Department of Psychology, University of Stirling, U.K.
R J
RJ
Baddeley
P J
PJ
Hancock
D006801:Humans; D008959:Models, Neurological; D008960:Models, Psychological; D016571:Neural Networks, Computer; D009949:Orientation; D014785:Vision, Ocular; D014796:Visual Perception