Fluorescence and Adaptation of Color Images

Abstract

Color plays a vitally important role in the world we live in. It surrounds us everywhere we go. Achromatic life, restricted to black, white and grey, is extremely dull. Color fascinates artists, for it adds enormously to aesthetic appreciation, directly invoking thoughts, emotions and feelings. Color fascinates scientists. For decades, scientists in color imaging, printing and digital photography have striven to satisfy increasing demands for accuracy in color reproduc- tion. Fluorescence is a very common phenomenon observed in many objects such as gems and corals, writing paper, clothes, and even laundry detergent. Traditional color imaging algo- rithms exclude fluorescence by assuming that all objects have only an ordinary reflective com- ponent. The first part of the thesis shows that the color appearance of an object with both reflective and fluorescent components can be represented as a linear combination of the two components. A linear model allows us to separate the two components using independent component analysis (ICA). We can then apply different algorithms to each component, and combine the results to form images with more accurate color. Displaying color images accurately is as important as reproducing color images accurately. The second part of the thesis presents a new, practical model for displaying color images on self-luminous displays such as LCD monitors. It shows that the model accounts for human visual system’s mixed adaptation condition and produces results comparable to many existing algorithms.