Color Impact 2023 was a great success. These pages are left here for archival purposes.

We hope to see you at a future Color Council meeting! Our next conference in June 2025.


June 11-15, 2023

Rochester Institute of Technology, Rochester, NY, USA


Presenter - Saeedeh Abasi


Saeedeh Abasi, PhD Student and Researcher

Modeling Hue Perception

Hue can be described with two types of scales. The first, for hue discrimination, is of the form of a hue angle metric such as found in the Munsell and CIELAB systems. The second, for hue appearance, is in the form of a hue quadrature metric as found in the NCS system and color appearance models such as CIECAM16. Any useful hue metric should also exhibit hue constancy. Hue angle in the IPT color model has repeatedly been shown to very well describe contours of constant hue and has been rigorously tested over more than two decades. However, the IPT model was not designed with hue spacing, for either discrimination or appearance, in mind. This presentation describes the derivation of a fundamental and physiologically plausible model, called FHS for Fundamental Hue Scales, with predictors for both hue discrimination and hue appearance built directly from cone fundamentals and with hue linearity as good as that found in IPT. The general model includes three steps. First step is to transform the XYZ to LMS if needed, which was done using the suggested matrix in IPT model. Other matrices such as the Hunt-Pointer-Estevez or the Guth can be used too. The second step is to build a color discrimination scale by calculating the initial opponent axes. This step gives the CIELAB-like hue angle and straight hue lines. Third step is introducing a simple transformation to rotate the opponent axes of second step. The result is orthogonal representation of the unique hues as a hue scale for color appearance models. This step directly gives the hue-quadrature type of metric. Such a model can be used with individual LMS color matching functions as the basis for the hue dimension of improved, and individualized, color appearance scales.

Bio

Saeedeh Abasi is a PhD student at the Munsell Color Science Laboratory at the Rochester Institute of Technology. She received her B.S., M.S. and PhD degrees in Textile Engineering from Amirkabir University of Technology. Her research interests are color science and image processing.  



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