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Related Experiment Video

Updated: Oct 31, 2025

Visualizing Visual Adaptation

Visualizing Visual Adaptation

Published on: April 24, 2017

Lightness Perception in Complex Scenes.

Richard F Murray¹

¹Department of Psychology and Centre for Vision Research, York University, Toronto M3J 1P3, Canada;

Annual Review of Vision Science

|July 1, 2021

Summary

This summary is machine-generated.

This review explores how humans perceive surface lightness in complex scenes. It highlights computational models and identifies future research directions for understanding achromatic color perception.

Keywords:

brightness human vision lightness modeling psychophysics

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Area of Science:

Visual Perception
Computational Psychology
Computer Vision

Background:

Lightness perception, the ability to see achromatic surface colors (black, white, grays), is crucial for visual tasks.
Perceiving surface color is challenging due to the inherent ambiguity of retinal images.
It has been a central research topic in experimental psychology for decades.

Purpose of the Study:

To review psychophysical research on lightness perception in complex scenes over the last 20 years.
To emphasize research supporting the development of computational models for lightness perception.
To identify and discuss open topics for future progress in the field.

Main Methods:

Review of psychophysical studies on lightness perception.
Analysis of computational models including Bayesian, equivalent illumination, and anchoring theories.
Integration of findings from computer vision and natural scene statistics.

Main Results:

A comprehensive overview of 20 years of research on lightness perception in complex visual environments.
Discussion of various computational approaches, such as Bayesian models, anchoring theory, and spatial filtering.
Identification of key areas for future research, including the lightness-brightness relationship.

Conclusions:

Significant progress has been made in understanding lightness perception through psychophysical and computational approaches.
Further development of sophisticated computational models is needed for complex scenes.
Investigating the relationship between lightness and brightness remains a key future direction.