Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

Color Science Seminar II is a weekly forum in which students will learn about current research topics in color science. The course focuses on journal club discussions of papers selected by the students and faculty. It also includes oral presentations from students, laboratory staff, and faculty as well as visiting speakers from within and external to RIT. Students will prepare their own oral presentations and written assignments based on the course readings and independent research. Students will further develop professional skills required for formal scientific presentations and writing. A draft thesis or dissertation proposal will also be prepared.

This asynchronous online course provides a technical introduction to color science and the CIE system of colorimetry. Topics covered include color perception, color measurement, color spaces, and applications. The course is intended for students with a technical background who are interested in adding an elective course in color science to their graduate program and for practitioners in the color field interested in a more thorough understanding of the science behind colorimetry. Cannot be taken for program credit by Color Science MS and PhD students.

This course covers the principles of color science including theory, application, and hands-on experience incorporated into the lectures. Topics include color appearance (hue, lightness, brightness, chroma, saturation, colorfulness), colorimetry (spectral, XYZ, xyY, L*a*b*, L*C*abhab, ∆E*ab, ∆E00), the use of linear algebra in color science and color imaging, metamerism, chromatic adaptation, color inconstancy, color rendering, color appearance models (CIECAM02), and image appearance models (S-CIELAB, iCAM).

Computational Vision Science This course provides an introduction to modern computer-based methods for the measurement and modeling of human vision. Lectures will introduce the experimental techniques of visual psychophysics including threshold measurement, psychometric functions, signal detection theory, and indirect, direct, and multidimensional scaling. Lectures will also introduce the MATLAB technical computing environment and will teach how to use MATLAB to run computer-based psychophysical experiments and to analyze experimental data and visualize results. Laboratory exercises will provide practical experience in using computer-based tools to conduct psychophysical experiments and to develop computational models of the results. Prior experience in vision science and/or scientific computing will be helpful but is not required.