Darkness filling-in: a neural model of darkness induction.

Abstract:

:A model of darkness induction based on a neural filling-in mechanism is proposed. The model borrows principles from both Land's Retinex theory and BCS/FCS filling-in model of Grossberg and colleagues. The main novel assumption of the induction model is that darkness filling-in signals, which originate at luminance borders, are partially blocked when they try to cross other borders. The percentage of the filling-in signal that is blocked is proportional to the log luminance ratio across the border that does the blocking. The model is used to give a quantitative account of the data from a brightness matching experiment in which a decremental test disk was surrounded by two concentric rings. The luminances of the rings were independently varied to modulate the brightness of the test. Observers adjusted the luminance of a comparison disk surrounded by a single ring of higher luminance to match the test disk in brightness.

journal_name

Vision Res

journal_title

Vision research

authors

Rudd ME,Arrington KF

doi

10.1016/s0042-6989(01)00216-4

subject

Has Abstract

pub_date

2001-12-01 00:00:00

pages

3649-62

issue

27

eissn

0042-6989

issn

1878-5646

pii

S0042-6989(01)00216-4

journal_volume

41

pub_type

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