Ph.D. Dissertation Defense: Hao Xie

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Color Science PHD Defense

Ph.D. Dissertation Defense
Representing Color as Multiple Independent Scales
Hao Xie
Color Science Ph.D. Candidate

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Abstract:
The concept of color space has served as a basis for vast scientific inquiries into the representation of color including colorimetry, psychology, and neuroscience. However, the ideal color space that can model both color appearance attributes and color difference as a uniform Euclidean space is still not yet available. In addition, different color appearance phenomena such as the Helmholtz-Kohlrausch effect highlight the interference or lack of independence between the existing color metrics. Based on the alternative representation of independent one-dimensional color scales and the concepts of brilliance and zero grayness proposed by Ralph Evans, a series of psychophysical experiments were designed and conducted to first collect G0 of equally bright colors by asking observers to adjust the luminance for a given chromaticity to the glowing threshold. The Helmholtz-Kohlrausch effect is thus automatically incorporated. G0 colors were found to correlate with the MacAdam optimal colors, which provides not only an ecologically relevant basis but also a computational handle for interpolating to other chromaticities. Further, the uniform brightness and saturation scales for five Munsell principal hues were collected via partition scaling, where the MacAdam optimal colors served as anchors. The independence relations between brightness and saturation were evaluated using maximum likelihood conjoint measurement. For the average observer, saturation as constant chromaticity is independent of luminance changes, while brightness receives a small positive contribution from excitation purity. This work further supports the feasibility of representing color as multiple independent scales that has wide implications for color vision modeling and color engineering, and provides the framework for further investigation of other color attributes.

Intended Audience: Experts.


Contact
Stephanie Livingston-Heywood
Event Snapshot
When and Where
April 17, 2023
3:00 pm - 4:00 pm
Room/Location: zoom
Who

Open to the Public

Interpreter Requested?

No

Topics
student experience