A Contrast- and Luminance-driven Multiscale Network Model of Brightness Perception Export

@article{Pessoa1995Contrast, abstract = {A neural network model of brightness perception is developed to account for a wide variety of data, including the classical phenomenon of Mach bands, low- and high-contrast missing fundamental, luminance staircases, and non-linear contrast effects associated with sinusoidal waveforms. The model builds upon previous work on filling-in models that produce brightness profiles through the interaction of boundary and feature signals. Boundary computations that are sensitive to luminance steps and to continuous luminance gradients are presented. A new interpretation of feature signals through the explicit representation of contrast-driven and luminance-driven information is provided and directly addresses the issue of brightness ” anchoring”. Computer simulations illustrate the model's competencies.}, author = {Pessoa, L. and Mingolla, E. and Neumann, H.}, citeulike-article-id = {4738935}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/0042-6989(94)00313-0}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/0042698994003130}, doi = {10.1016/0042-6989(94)00313-0}, issn = {00426989}, journal = {Vision Research}, keywords = {bcs, boundary, brightness, facade, feedback, fillingin, gradient, simulation, theory, v1, v2, web}, month = {August}, number = {15}, pages = {2201--2223}, posted-at = {2009-06-04 02:31:29}, priority = {5}, title = {A Contrast- and Luminance-driven Multiscale Network Model of Brightness Perception}, url = {http://dx.doi.org/10.1016/0042-6989(94)00313-0}, volume = {35}, year = {1995} }

TY - JOUR ID - Pessoa1995Contrast L3 - citeulike-article-id:4738935 N2 - A neural network model of brightness perception is developed to account for a wide variety of data, including the classical phenomenon of Mach bands, low- and high-contrast missing fundamental, luminance staircases, and non-linear contrast effects associated with sinusoidal waveforms. The model builds upon previous work on filling-in models that produce brightness profiles through the interaction of boundary and feature signals. Boundary computations that are sensitive to luminance steps and to continuous luminance gradients are presented. A new interpretation of feature signals through the explicit representation of contrast-driven and luminance-driven information is provided and directly addresses the issue of brightness “anchoring”. Computer simulations illustrate the model's competencies. IS - 15 JF - Vision Research SN - 00426989 EP - 2223 TI - A Contrast- and Luminance-driven Multiscale Network Model of Brightness Perception VL - 35 SP - 2201 KW - bcs KW - boundary KW - brightness KW - facade KW - feedback KW - fillingin KW - gradient KW - simulation KW - theory KW - v1 KW - v2 KW - web AU - Pessoa, L AU - Mingolla, E AU - Neumann, H PY - 1995/08// UR - http://dx.doi.org/10.1016/0042-6989(94)00313-0 ER -