Foundations of VisionDesigned for students, scientists and engineers interested in learning about the core ideas of vision science, this volume brings together the broad range of data and theory accumulated in this field. |
Contents
2 Image Formation | 13 |
A Guide to the Principles of and Superposition | 22 |
Table of Contents | 27 |
Copyright | |
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algorithms area V1 Bayes classifier behavioral brain Chapter coefficients color appearance color-matching experiment color-matching functions columns components computational cone absorptions contrast contrast-sensitivity function convolution convolution kernel cortical cosinusoids curves encoding Equation estimate experimental fovea frame-buffer harmonic functions Hubel human illumination input intensity layers lens linear model linespread function magnocellular match measurements methods motion perception multiresolution neural image neurons nonlinear object observer ocular dominance columns one-dimensional optical orientation output parvocellular phosphors photopigment photoreceptors pixels predict primary lights properties pyramid receptive fields receptive-field reflected region relative represent representation response retinal disparity retinal ganglion cells retinal image S-cones sampling scotopic sensitivity sensors shift-invariant shown in Figure shows signal sinusoidal space-time spatial frequency spatial pattern spectral power distribution stimulus surface system matrix test light theory threshold tion transformation values vector Vision Res visual cortex visual pathways visual streams visual system wavelength