Instructors: Thrasyvoulos N. Pappas, Northwestern University, and Sheila Hemami, Triple Ring Technologies
Level: Intermediate
Duration: 4 hours
Prerequisites: A basic understanding of image compression algorithms  and background in digital signal processing and basic statistics: frequency-based representations, filtering, distributions.

Benefits:
This course enables the attendee to:

• Gain a basic understanding of the properties of the human visual system and current applications (image and video compression, restoration, retrieval, etc.) that attempt to exploit these properties.
• Understand current distortion models for different applications, and how they can be used to modify or develop new metrics for specific contexts.
• Understand the differences between sub-threshold and supra-threshold artifacts, the HVS responses to these two paradigms, and the differences in measuring these responses.
• Understand the capabilities and limitations of full-reference, limited-reference, and no-reference metrics, and why each might be used in a particular application.

Course Description:
This course examines objective criteria for image quality based on models of visual perception. The primary emphasis is on fidelity but the instructors will broaden the scope to include structural equivalence. They also discuss no-reference, limited-reference, and neural-net-based metrics. They examine applications with emphasis on image and video compression. They also examine near-threshold perceptual metrics, which estimate just-noticeable distortion thresholds, and supra-threshold metrics. The instructors also consider metrics for structural equivalence, whereby the original and the distorted image have visible differences but both are of high visual quality. Further examination includes procedures for evaluating the performance of quality metrics, including database design, models for generating realistic distortions, and subjective procedures for metric development and testing. The instructors discuss the state-of-the-art and directions for future research.

Intended Audience:

• Image and video compression specialists who wish to gain an understanding of how performance can be quantified.
• Engineers and scientists who wish to learn about objective image and video quality evaluation.
• Managers who wish to gain a solid overview of image and video quality evaluation.
• Students who wish to pursue a career in digital image processing.
• Intellectual property and patent attorneys who wish to gain a more fundamental understanding of quality metrics and the underlying technologies.
• Government laboratory personnel who work in imaging.

Thrasyvoulos N. Pappas received his SB, SM, and PhD in electrical engineering and computer science from MIT. From 1987 until 1999, he was a member of the technical staff at Bell Laboratories; he is currently a professor in the Department of Electrical and Computer Engineering at Northwestern University. His research interests are in image and video quality and compression, image and video analysis, content-based retrieval, perceptual models for multimedia processing, model-based halftoning, and tactile and multimodal interfaces. Pappas has served as vice-president publications IEEE Signal Processing Society, editor-in-chief of the IEEE Transactions on Image Processing , elected member of the Board of Governors of the Signal Processing Society of IEEE, chair of the IEEE Image and Multidimensional Signal Processing (now IVMSP) Technical Committee, technical program co-chair of ICIP-01 and ICIP-09, and co-chair of the 2011 IEEE IVMSP Workshop on Perception and Visual Analysis. He has also served as co-chair of the SPIE/IS&T Electronic Imaging Symposium and co-chair of the EI Conference on Human Vision and Electronic Imaging. He is currently co-editor-in-chief of the IS&T Journal of Perceptual Imaging. Pappas is a Fellow of IEEE, SPIE, and IS&T.

Sheila Hemami holds a BSEE from the University of Michigan, and an MSEE and PhD from Stanford University. She worked at Hewlett-Packard Laboratories and was a professor and associate director of the School of Electrical and Computer Engineering at Cornell University and professor and chair of the Department of Electrical & Computer Engineering at Northeastern University. More recently, she was director of strategic technical opportunities at the Charles Stark Draper Laboratory, where she created and led a new business unit dedicated to large-scale challenges for the environment and for under-served medical populations. In 2021, she joined Triple Ring Technologies to lead the company’s Boston office. Hemami's research interests broadly concern communication of visual information from the perspectives of both signal processing and psychophysics. She has held various visiting positions, most recently at INRIA Bretagne in Rennes, France. She was elected a Fellow of the IEEE in 2009 for her contributions to robust and perceptual image and video communications. She has received numerous university and national teaching awards, including Eta Kappa Nu's C. Holmes MacDonald Award. She served as an IEEE vice-president publications products and services, was a distinguished lecturer for the IEEE Signal Processing Society, and editor-in-chief for the IEEE Transactions on Multimedia. She has held various technical leadership positions in the IEEE.