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Updated: Jun 21, 2026

Visualizing Visual Adaptation

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Published on: April 24, 2017

Brightness induction from uniform and complex surrounds: a general model

B Spehar¹, J S Debonet, Q Zaidi

¹SUNY College of Optometry, NY 10010, USA.

Vision Research

|July 1, 1996

Summary

This summary is machine-generated.

Brightness perception from complex surrounds was studied using modulated dot textures. A model explains brightness induction via weighted spatial summation and luminance gain control, improving understanding of visual processing.

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Area of Science:

Visual perception
Computational neuroscience
Color science

Background:

Understanding brightness induction is crucial for visual perception.
Complex surrounds, unlike simple ones, present challenges in predicting brightness perception.
Previous models often simplify surround complexity, limiting their applicability.

Purpose of the Study:

To investigate brightness induction from complex, non-figural achromatic surrounds.
To develop and validate a computational model for brightness induction in such conditions.
To explore the role of luminance and contrast modulation in the surround.

Main Methods:

A spatially uniform test field was surrounded by a random texture of two sinusoidally modulated dot sets.
Independent control of mean luminance, phase, and modulation amplitude for each dot set.
Brightness induction measured using a modulation nulling technique.

Main Results:

Brightness induction was successfully measured under complex surround conditions.
A model based on weighted spatial summation of induced effects provided a good fit to the data.
The model incorporated local luminance gain controls in both test and surround fields.

Conclusions:

Brightness induction from complex surrounds can be modeled by summing individual element effects.
Luminance gain control, influenced by luminance differences, is a key mechanism.
The findings advance our understanding of how the visual system processes complex visual scenes.