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.
Baddeley
R J
RJ
Department of Psychology, University of Stirling, U.K.
Hancock
P J
PJ
D006801:Humans; D008959:Models, Neurological; D008960:Models, Psychological; D016571:Neural Networks, Computer; D009949:Orientation; D014785:Vision, Ocular; D014796:Visual Perception