Advanced Colorimetry and Color Appearance
Instructor: Gaurav Sharma, University of Rochester
Level: Intermediate
Duration: 4 Hours
Course Time: ON DEMAND view recording on your own time

Course Prerequisite: Prior knowledge of fundamentals of colorimetry is assumed. The presumed background is at the level covered in CIC SC01 Color and Imaging.

Benefits:
Attendees will be able to:

• Explain how changes in the state of visual adaptation affect the perceived appearance of colors.
• List the main elements of a color appearance model and explain the critical role of chromatic adaptation.
• Describe the Von Kries framework commonly employed for chromatic adaptation transformations and perform computations using the model.
• Explain how the CIECAM02/CAM16 color appearance models compute color appearance correlates from colorimetry and viewing condition specifications and to obtain corresponding colorimetric representations for different viewing conditions.
• List commonly employed color appearance models and explain how relevant parameters for these models are determined for real-world viewing environments.
• Describe the components of spatial color appearance models and highlight the interactions between color and spatial perception.

Course Description
Building upon a foundation in basic color science and colorimetry, this course provides attendees a broad understanding of color appearance phenomena and introduces them to color appearance modeling. Several important color appearance phenomena are introduced and their relation to changes in the state of adaptation of the human visual system is explained. The perceptual color attributes of lightness, brightness, colorfulness, saturation, chroma, and hue are defined and explained. Common computational models for evaluating correlates of these attributes are presented. Spatial aspects of color vision are discussed and simple models for spatial color perception are summarized.

Intended Audience: color engineers, research scientists, and software developers involved in design and optimization of color imaging systems, algorithms, and devices.

Gaurav Sharma has more than 25 years of experience in the design and optimization of color imaging systems and algorithms that spans employment at the Xerox Innovation Group and his current position as a professor at the University of Rochester in the Departments of Electrical and Computer Engineering and of Computer Science. Additionally, he has consulted for several companies on the development of new imaging systems and algorithms. He holds 54 issued patents and has authored more than 200 peer-reviewed publications. He is the editor of the Digital Color Imaging Handbook (CRC Press) and served as the editor-in-chief for the SPIE/IS&T Journal of Electronic Imaging (2011-2015) and for the IEEE Transactions on Image Processing (2018-2020). Sharma is a fellow of IS&T, IEEE, and SPIE.

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