Refinement of a model for predicting perceived brightness

Ulrich Eisemann

doi:10.1117/12.453012

28 December 2001 Refinement of a model for predicting perceived brightness

Ulrich Eisemann

Proceedings Volume 4663, Color Imaging: Device-Independent Color, Color Hardcopy, and Applications VII; (2001) https://doi.org/10.1117/12.453012
Event: Electronic Imaging, 2002, San Jose, California, United States

Abstract

In this paper, an updated version of a previously proposed model for the prediction of perceived brightness is presented. The model is not only applicable to simple spatial configurations but also to complex scenes and relies entirely on physical and colorimetric data. These are derived from a complex description of the entire scene which eliminates the need for a priori knowledge like the popular reference white concept and others. The model includes an extensive preprocessing stage consisting of a central projection to transform the scene description into a pixel-oriented image, a simple pixel classification to identify the stimulus region and extensive histogram calculations to extract quantiles as characteristic features. Based on the quantiles, which form the output of the preprocessing stage and represent the distribution of luminance levels within the scene, a map has been implemented to calculate a value characterizing the perceived brightness. The development of the model structure was inspired by a series of haploscopic brightness matching experiments, whose experimental data were also used to train and test the model. The results are quite encouraging because the differences between experimental and model-predicted brightness values rarely exceed the range of the natural inter-observer deviations.

Citation Download Citation

Ulrich Eisemann "Refinement of a model for predicting perceived brightness", Proc. SPIE 4663, Color Imaging: Device-Independent Color, Color Hardcopy, and Applications VII, (28 December 2001); https://doi.org/10.1117/12.453012

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KEYWORDS

Data modeling

Image segmentation

Eye

Image classification

Visual process modeling

Bismuth

Eye models

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