Image Quality: The Systems View

Image, print, picture and display quality are often considered "subjective" and in the "eye of the beholder." with the implication that image quality cannot be put on a quantitative footing. Compounding this confusion is that the concept of image quality depends on where you view the problem. A process engineer will feel that it's the process that controls the image quality. Developers of image processing algorithms feel that image processing is where the action is. Of course, both areas contribute to image quality.

Image Quality: The Systems View puts the various pieces together in a unified way–the systems perspective. Using the Image Quality Circle; this course paints the big-picture view of image quality. The Image Quality Circle (IQC) is a practical and useful tool that is used by major imaging hardware consumables manufacturers.

The goals of this two-day course are:

• To give attendees a comprehensive understanding of the concept of image/print quality;
• To help the attendees use the Image Quality Circle as a process for managing and developing the image/print quality of imaging and consumable products.

At the end of the course you will:

• Understand image quality and how it fits into the Image Quality Circle framework;
• Understand the basic requirements for image measurements;
• Be able to conduct simple psychometric image scaling studies;
• Connect image measurement to visual percepts;
• Be able to write image quality product specifications/requirements.

Course Outline

Day One

The Image Quality Circle–a process to manage image quality

• What is image/print quality?
• Introduction to the Image Quality Circle

Image Scaling–Measuring Human/Customer Response to Images

• Scale types
• Scaling methods
• Data collection and analysis

Attributes of image/print quality–The "Nesses"

• Pictorial/complex image/photographic attributes
• Image compression attributes/artifacts
• Text/line/graphics attributes
• Illustrations of common attributes

Image Quality Models

• Basic considerations
• Generalized Weighted Mean Hypothesis model
• Model construction

Day Two

Visual Algorithms–Connecting the Attributes to Image Measurements

• Human visual system properties
• Visual system models for algorithm development
• Algorithm construction

Image Measurements–Physical Image Parameters

• Machine vision, a.k.a. densitometry–historical review
• Spectral response–colorimetry
• Optical considerations–Modulation Transfer Function
• Desktop scanners and digital cameras as image measurement instruments

System Models–Connecting Image Measurement to Technology Variables

• Macro–large area–imaging models
• Micro imaging models–reflectance mean, variance

Technology Variables–the "Nesses" They Influence

Applications, $, and Specifications within the IQC

• Scale overlay concept
• Managing image quality and image quality specifications
• An image quality specification process

Course Director and Instructor

Peter Engeldrum, the inventor of the Image Quality Circle (IQC), will be the course instructor. He is president of Imcotek, a technical consulting firm that assists organizations in finding solutions to imaging system and image and color problems. With over 25 years of experience in imaging and color systems, he has worked with a wide variety of imaging and display technologies. Peter has been active in the the areas of image and color quality, color scanning, color printing, photography, and color imaging over the Internet. Mr. Engeldrum was a faculty member at the Center for Imaging Science, Rochester Institute of Technology, where he received his degrees. Peter is a member of several professional societies and is a Fellow of IS&T. He has also served on several corporate advisory boards and has several patents and patents pending in the areas of display calibration and Internet imaging.

For further information email Peter Engeldrum or call: (781)-756-0935.

Imcotek
P.O. Box 17
Winchester, MA 01890

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