Detection of Changes in Luminance Distributions

Overview

Journal J Vis

Specialty Ophthalmology

Date 2011 Nov 17

PMID 22085597

Citations 3

Authors

Thomas Y Lee

David H Brainard

Affiliations

Soon will be listed here.

Abstract

How well can observers detect the presence of a change in luminance distributions? Performance was measured in three experiments. Observers viewed pairs of grayscale images on a calibrated CRT display. Each image was a checkerboard. All luminances in one image of each pair consisted of random draws from a single probability distribution. For the other image, some patch luminances consisted of random draws from that same distribution, while the rest of the patch luminances (test patches) consisted of random draws from a second distribution. The observers' task was to pick the image with luminances drawn from two distributions. The parameters of the second distribution that led to 75% correct performance were determined across manipulations of (1) the number of test patches, (2) the observers' certainty about test patch location, and (3) the geometric structure of the images. Performance improved with number of test patches and location certainty. The geometric manipulations did not affect performance. An ideal observer model with high efficiency fit the data well and a classification image analysis showed a similar use of information by the ideal and human observers, indicating that observers can make effective use of photometric information in our distribution discrimination task.

Citing Articles

Computational-observer analysis of illumination discrimination.

Ding X, Radonjic A, Cottaris N, Jiang H, Wandell B, Brainard D J Vis. 2019; 19(7):11.

PMID: 31323097 PMC: 6645618. DOI: 10.1167/19.7.11.

Human vision is attuned to the diffuseness of natural light.

Morgenstern Y, Geisler W, Murray R J Vis. 2014; 14(9).

PMID: 25139864 PMC: 4141658. DOI: 10.1167/14.9.15.

A Bayesian model of lightness perception that incorporates spatial variation in the illumination.

Allred S, Brainard D J Vis. 2013; 13(7):18.

PMID: 23814073 PMC: 3697904. DOI: 10.1167/13.7.18.

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