MCSL Industrial Short Courses - Course Details

FUNDAMENTALS OF COLOR SCIENCE

June 5-6, 2012 

Understanding Color (Mark Fairchild)

Color is familiar to most, but seldom described scientifically in our daily activities. This session reviews the definition of color as a human perception along with the attributes used to describe color (i.e., brightness, lightness, colorfulness, chroma, saturation, and hue). These attributes are demonstrated visually and defined technically to set the stage for the remainder of the course. One of the main aims of color science is to describe and predict these perceptions through physical measurements and mathematical modeling of the human visual response. Color order systems (e.g., Munsell and NCS) are also introduced as a method to specify color.

Color Vision (James Ferwerda)

Understanding color perception is an essential part of Color Science. This lecture will provide an introduction to the study of visual perception. First, the structure of the visual system will be described to show how the “hardware” of vision constrains what we see. Next functional aspects of vision such as pattern, motion, depth, and (not least) color perception will be described, to understand the capabilities and limitations of human visual performance. Throughout the lecture, examples will illustrate how fundamental findings in the science of visual perception have informed the development of color science and technology.

CIE Color Spaces (Roy Berns)

In commerce, color is communicated numerically, the numbers relating to what we see. This lecture will begin with the fundamental experiments from the early 20^th century leading to photometric (luminance and illuminance) and colorimetric (tristimulus values, XYZ, and chromaticities, xy) color specification. The desire to use these numbers as a “ruler” to set tolerances led to new color spaces. This historical path from XYZ to CIELAB is presented. CIELAB is considered in detail including L*a*b*, L*C*_abh_ab, ∆L*∆a*∆b*, and ∆L*∆C*_ab∆H*_ab. We will end with the strengths and weaknesses of CIELAB and current international activities to “retire” CIELAB.

Color Measurements (Dave Wyble)

The most fundamental measurements of color are based on spectral properties. Spectrophotometers measure spectral reflectance, quantifying object color, while spectroradiometers measure spectral radiance, quantifying lighting color. This lecture will cover the basic operation and construction of both types of instruments. Other methods of object color evaluation will be described including gloss and multi-angle measurements. To evaluate instruments, the concepts of precision and accuracy of measurement devices will be introduced, along with the related topic of instrument profiling.

Setting Color Tolerances (Roy S. Berns)

“Color differences below 1.0 are acceptable (good) while values above are rejected (bad).” If only this were true or this simplistic. This lecture will begin with the concept of a weighted color-difference formula to correct well-known limitations of CIELAB in predicting perceived color differences. This approach resulted in the CMC, CIE94, and CIEDE2000 formulas. CIEDE2000 (ugly) will be explained in detail. Tolerances should not be treated as absolute truth; there is considerable uncertainty both in visual judgments and formulas. We will conclude with methods of setting tolerances and their proper usage.

Beyond Color: Gloss and Texture (James Ferwerda)

Color is one component of overall surface appearance. Other attributes include gloss, pattern, texture, and translucency. This lecture will survey the topic of overall surface appearance, starting with a discussion of the bi-directional reflectance distribution function (BRDF) that characterizes how light is scattered by a surface.  Next, methods for measuring surface BRDFs will be described, and the characteristics of gonioreflectometers and glossmeters will be discussed. The need for spatially-varying measurements of complex surfaces, and methods for image-based appearance capture will then be surveyed. Finally, computer graphics techniques for accurately simulating surface appearance will be introduced.

Color and Illumination (Mark Fairchild)

Illumination is a key component of color perception and measurement since without light, there is no color perception of objects. This session examines the importance of illumination and the techniques that are used to measure, specify, and simulate lighting and the effects of illumination on color. CIE Illuminants (e.g. A, D65, F11, etc.) are defined and described along with fundamental measurements such as radiance, irradiance, luminance, illuminance, and color temperature. Illumination effects are further explored through metamerism, chromatic, adaptation, and luminance-dependent appearance effects along with metrics such as indices of metamerism, color rendering, and color inconstancy.

Color Imaging (Jinwei Gu)

Everyday we interact with various types of devices that capture (e.g., scanners, cameras), display (e.g., monitors, projectors), or reproduce color (e.g., printers). How can these devices talk to each other correctly so that the color in the output will be as faithful as the color in the input? This lecture will give you an in-depth overview of color management. We will first briefly review color imaging and reproduction. We will then introduce color management and show how to build color profiles. We will conclude with a demonstration that shows how color management makes color flow smoothly and predictably – from capture, through editing, and to the final output.

ADVANCED TOPICS IN COLOR AND IMAGING

June 7, 2012 

Basic methods of colorimetry (e.g., CIE XYZ and CIELAB) function to specify average color matches and color differences in very limited viewing conditions. However, it is well known that the appearance of color depends on many properties of the viewing environment that are not treated in basic colorimetric techniques. These include changes in background, surround, illumination level, and illumination color. Color appearance models aim to extend basic colorimetry to begin to predict appearance across changes in viewing conditions. This session introduces the concepts of color appearance phenomena, defines chromatic adaptation and color appearance models, and provides an overview of the CIECAM02 color appearance model.

Image Appearance (Mark Fairchild)

In applications such as image quality specification and image rendering, color appearance models do not address important spatial and temporal aspects of human color perception such as local adaptation and ability to resolve details or noise. This session describes those issues along with a framework to begin to address image quality issues through spatial filtering of images and image rendering issues, such as HDR tone mapping, through simulation of local adaptation. This concept of “image appearance modeling” extends color appearance modeling to even more complex visual stimuli and sets the stage for beginning to understand further dimensions of color perception.

Psychophysical Methods in Color Science (James Ferwerda)

Findings from psychophysical experiments have informed the development of virtually all aspects of color science and technology. This course will survey the concepts and methods of visual psychophysics. First, classical techniques for measuring visual thresholds will be introduced. Thurstonian methods for suprathreshold scaling will then be described, followed by a discussion of modern direct and multidimensional scaling techniques. Throughout the lecture practical examples of designing perceptual experiments and analyzing the results will be presented. The goal of this course is to provide knowledge of the scientific methods available for quantifying the relationships between object properties and their visual appearances.

Surface Appearance Capture and Rendering (Jinwei Gu)

Traditional gonio-systems and spectrophotometers are expensive and time-consuming for measuring material appearance. Most existing monitors and printers are limited to reproduce material appearance at a fixed lighting and viewing condition.  In this lecture, we will survey recent advances in computational photography that use programmable illuminations and sensors to build next-generation imaging, display, and printing devices that go beyond these limits. We will cover topics including catadioptic imaging and structured light systems for efficiently measuring material properties, light sensitive displays and light field displays, and printers that can fabricate material properties beyond color.

Instrumental-Based Color Matching

June 7, 2012

Optical Models for Reflecting Materials

Optical models are used to relate a colorant formula (recipe) with its resulting color, defined spectrally and colorimetrically. The Kubelka-Munk model will be described including transparent, translucent, and opaque forms. Linearity and additivity of absorption and scattering lead to the relationship between concentration and spectra of a mixture. The Saunderson correction is included to account for refractive index differences. An introduction to multiple-flux models finishes the lecture.

Colorant Database Development and Evaluation

Once an optical model is selected, the model parameters are determined for each colorant by preparing samples at multiple concentrations (tints). We will form laboratory teams and produce and measure the spectral reflectance factor of several tint ladders for an opaque paint system. Using an Excel spreadsheet created for this short course, optical constants will be estimated including spectral absorption, spectral scattering, and diffuse and collimated Saunderson terms. Spectral accuracy and linearity will be evaluated.

Spectral and Colorimetric Matching Algorithms

A recipe can be optimized for spectral matching, minimal color difference for one or more illuminants, metamerism, color inconstancy, and cost. The process can be divided into two components: colorant selection and recipe prediction. An overview of optimization is presented enabling recipe prediction for these matching goals (objective functions). The Excel spreadsheet will be used to evaluate the tradeoffs in match quality between these different goals.

Matching Evaluation and Batch Correction

Metameric and non-metameric unknowns will be given to each laboratory team to match using the Excel spreadsheet. Based on the first samples produced, batch correction will be used to improve the recipe accuracy. The team producing the best matches will win a color science prize.