Color Science Thesis Defense: Improved Colorimetry Through Fundamental Appearance Scales
Color Science Thesis Defense
Improved Colorimetry Through Fundamental Appearance Scales
Saeedeh Abasi
Color Science Ph.D. Candidate
Rochester Institute of Technology
Event Details:
This dissertation introduces a new framework for color appearance modeling, referred to as the Fundamental Color Appearance Model (FCAM). The primary objective of this work is to develop perceptually meaningful color appearance scales that are directly derived from cone fundamentals and formulated as independent one-dimensional scales. Unlike conventional color appearance models that rely on complex three-dimensional color spaces and extensive nonlinear processing, FCAM describes color appearance attributes individually through mathematically simple and physiologically grounded formulations. FCAM consists of four independent one-dimensional scales: the Fundamental Hue Scale (FHS), Fundamental Lightness Scale (FLS), Fundamental Brightness Scale (FBS), and Fundamental Saturation Scale (FSS). Each scale is derived directly from LMS cone responses and can incorporate chromatic adaptation in a straightforward manner. This structure reflects the perceptual independence of color appearance attributes and avoids assumptions about an underlying multidimensional geometry. The proposed scales were evaluated using a wide range of existing psychophysical data sets as well as newly collected experimental data. Results demonstrate that the fundamental one-dimensional scales achieve performance that is comparable to, and in some cases exceeds, that of established and more complex color appearance models. Despite their simplicity, the proposed scales successfully predict key perceptual properties such as hue linearity and spacing, lightness and brightness behavior under varying viewing conditions, and saturation constancy across hue and luminance changes. An important achievement of this research is the flexibility of the proposed one-dimensional framework. Each scale can be optimized independently using new or application-specific data sets without affecting the remaining attributes. This modular structure allows FCAM to be adapted to different observers, viewing conditions, and emerging display technologies while maintaining computational efficiency and conceptual clarity. Overall, this dissertation demonstrates that accurate color appearance prediction does not require highly complex mathematical models. Instead, perceptually effective and physiologically meaningful color appearance modeling can be achieved through simple, independent, and adaptable one-dimensional scales derived directly from cone fundamentals.
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