AI Article Synopsis
- The research investigates how texture segregation works in visual perception, revealing that nonlinearity in static pattern vision isn't just an early or late gain control process.
- This suggests the involvement of inhibition between different channels, similar to what's seen in a normalization network.
- While both complex and simple channels are affected by this normalization, it's still unclear if the outputs from complex channels contribute to the normalization pool.
Article Abstract
Results from two types of texture-segregation experiments considered jointly demonstrate that the heavily-compressive intensive nonlinearity acting in static pattern vision is not a relatively early, local gain control like light adaptation in the retina or LGN. Nor can it be a late, within-channel contrast-gain control. All the results suggest that it is inhibition among channels as in a normalization network. The normalization pool affects the complex-channel (second-order, non-Fourier) pathway in the same manner in which it affects the simple-channel (first-order, Fourier) pathway, but it is not yet known whether complex channels' outputs are part of the normalization pool.
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| http://dx.doi.org/10.1016/s0042-6989(00)00123-1 | DOI Listing |
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