Solving Color Problems using Vector Space Arithmetic
Instructor: Michael Vrhel, Artifex Software, Inc.
Level:  Intermediate
Duration: 2 hours plus 15 minute break. After the class, adjourn to Zoom to join the instructor and other students in a discussion of the class.
Course Time:
    New York: Tuesday 10 November, 18:30-20:45
    Paris: Wednesday 11 November, 00:30-02:45
    Tokyo: Wednesday 11 November, 8:30-10:45

Benefits:
Attendees will be able to:

• Understand the matrix-vector equations often seen at color conferences and in color journals.
• Express their own color systems in terms of vectors and matrices as well as know when it is appropriate to do so.
• Determine closed form solutions to optimization problems in color.
• Implement their models in MATLAB and apply numerical optimization methods.

Intended Audience: engineers, students, and those wishing to have a firmer understanding of the mathematical modeling and optimization of color systems.

Course Description:
Matrices and vectors have been used for decades to model color technologies. Besides allowing the modeling of complex systems, this notation is readily implemented in vector-based languages like MATLAB. For some, this material can be overwhelming. The goal of the course is to make this approach to color science problems accessible to everyone. We first review the basics of matrices and vectors including the conditions under which this notation can be used for color systems. Models in the area of color recording, reproduction, measurement and transformation are covered. A review of optimization methods is made including the determination of closed form solutions. For those problems that cannot be solved directly, numerical methods are required. In these cases, we turn to the use of MATLAB to model example systems. With the models in place, we demonstrate the use of MATLAB’s optimization methods to determine a solution.

Michael Vrhel has more than 30 years’ experience in color imaging. He received a PhD in electrical engineering from North Carolina State University. During his PhD studies he was a Kodak Fellow. He was a Research Associate with the National Research Council and has held positions at Color Savvy Systems, Conexant Systems, TAK Imaging, Pagemark Technology and Artifex Software. He is the co-author of The Fundamental of Digital Imaging (Cambridge University Press).

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