Color Management 12/07/06 Color management systems really do only two things 1.Change the values of pixels to keep the color consistent across different devices 2.Describe the color of pixels But nobody said that it would be easy!

Color Management Tools A Reference color space Represents color as we “see” it. Device profiles Describes a device's color behavior in terms of RGB or CMYK values Color engines Software that does the actual work of matching color from device to device

Color Management Goal Every digital color reproduction application is judged on how well it appears to the end user. The quality metric for any visual reproduction device, system, or application must be based on the Human Visual System (HVS). –One component of HVS is color perception. –Over 40 percent of the human brain is spent interpreting visual information –No complete model of the human visual system.

What is Color? One of the fundamental truths about color that's important to understand is that color is something we humans impose on the world. The world isn't colored; we just see it that way.

Working definition of color Our response to different wave lengths of light –We create the color as a response to that light, just as we create the sensation of pain when struck by an object –We can't really measure color itself -- just as we can't measure pain –What we're really measuring is the stimulus that creates it -- something like measuring the motion and mass of the pebble

Working Color Definition cont’d The different wavelengths of light aren't really colored, they're simply electromagnetic waves with a known length and amount of energy Our perceptual system gives them the attribute of color.. Our eyes contain two types of light sensitive sensors: rods and cones Rods are panchromatic, and don't contribute to color vision. Color sensation comes from the cone sensors. Our eyes contain three different types of cones, which are most properly referred to as the L, M, and S cones, denoting cones sensitive to long, medium short wavelengths of light.

Working Color Definition cont’d Cones respond to light in a complex manner; unlike the sensors in a scanner or digital camera, where each sensor simply records the amount of (filtered) light it receives. The cones feed into a processing system that not only receives the signal from each cone, but also compares each signal to that of its neighbors, and assigns weighting to the raw signals. Weighting is necessary because we have many more L and M cones than S cones. The relative population of the L, M, and S cones is approximately 40:20:1. The weighted response is approximately 30:59:11

Working Color Definition cont’d The figure shows the cones' raw sensitivities to differing wavelengths The horizontal (x) axis shows wavelengths, and the vertical (y) axis depicts the intensity of cone response to each wavelength Labeling them R, G, and B would be incorrect. Note the overlap between the cones’ sensitivities

CIE 1931 Standard Observer The CIE 1931 (Commission Internationale de l'Eclairage) Standard Observer represents the color perception of a "normal" person. The curves show the intensity of X, Y, and Z values (akin to cone response) for a given wavelength It shows how our eyes receive continuous spectra as stimuli, and convert those continuous spectra into varying amounts of three different primaries,

CIE 1931 Standard Observer Cont’d CIE XYZ lies at the heart of all current implementations of color management: –CIE XYZ and its close cousin CIE LAB (derived from CIE XYZ) define well-known, light- independent, device-independent color spaces that software, device profiles, and drivers use to interpret and translate color information.

CIE 1931 Standard Observer Cont’d Note that each of the three responses cover a wide band of wavelengths, with a lot of overlap. In fact, there are a near infinite number of combinations of the visible spectrum that can create the same visual response i.e. color. –The broadband response of our eyes' cones is what makes color matching possible: It's much, much easier to achieve samples that yield the same CIE XYZ values than to duplicate precisely the same spectral distribution.

CIE 1931 Standard Observer Cont’d Now the bad news – –Unfortunately, it’s also true that no real world system yet provides the combination of stimuli needed to cover the complete gamut of color that we can see. –Broadband response also contributes Mesmerism Two color samples appear to match under one light source but differ under another

Mesmerism Example Two samples viewed under a 6500 K light: The same samples viewed under an incandescent light

Color Summary Most important, color is something that happens in our heads. We can’t measure color. We only measure the stimulus - - color is our response. Second,real-world color matching is highly dependent on the light source under which the match is judged. If you know your work will appear under dramatically different lighting conditions, either make adjustments or be prepared for disappointment. Third the science on which color management is based isn’t a complete description of human color perception. The models and tools we use today may produce results that our senses tell us are unacceptable. When the tools tell us one thing and our eyes tell us another, we should let our eyes be the final judge.

Color Space It’s really 3 dimensional –RBG > Red, Blue, Green –HSB > Hue, Saturation, Brightness –CMY > Cyan, Magenta, Yellow (+ black “crutch” added) –LAB > Luminance, A ( Red-Green axis ) B ( Blue-Yellow axis )

Color Space Cont’d Rotated 180 degrees about the vertical (neutral) axis For convenience a particular color space is often shown as a “2-D slice”, at 50% luminance, but the entire “3-D” space is used in color management. 3-D CIE LAB space

Reference Color Spaces CIE X-Y space (50%) CIE U’-V’ space (50%) CIE A-B space (50%) Each of the CIE spaces are derived from The CIE Tri-Stimulus response discussed earlier. They show the HVS Gamut (at 50% luminosity) referred to as the Reference Color Space. It is “Device independent”. The CIE A-B space (also known as LAB) is favored in digital color management because CIE colors extend equally on two axes, and distributes colors roughly proportional to their perceived color differences.

Reference Color space Cont’d The LAB spaces below show the (small) S-RGB gamut, the larger Adobe RGB gamut and two ink jet printer’s gamut 25% luminance Fuji Frontier 50% Canon I % Commercial Ink Jet Consumer Ink Jet CMYK Gamut (shown) is the standard color print press gamut, which extends outside beyond the S-RGB (Monitor Display) gamut for some colors, but is contained within the Adobe RGB gamut which is why Adobe RGB was created

Device Profiles Device profiles provide us with descriptions of the way color devices behave. A device profile is basically akin to a dual-language dictionary –One language being the actual perceived color in the reference (LAB or XYZ) space –The other being the device-specific RGB or CMYK space. The device profiles correlate the device control signals -- the RGB or CMYK values -- with the actual perceived color (expressed as LAB or XYZ values) that they produce.

Device Profiles Cont’d Profiles are useful in two ways 1.When we associate a device profile with a set of device- specific RGB or CMYK color values, we can use the profile to determine what actual color the values represent in the CIE reference space (X,Y,Z or L,A,B) 2.When we know the actual color we're trying to reproduce (in XYZ or LAB), we can look at the profile for the device on which we're trying to reproduce that color and then determine what device-specific RGB or CMYK values the device needs to reproduce that color. For example, a digital camera has a RGB profile that allows a Color Management module to accurately create a LAB value for each pixel (step 1). In turn, that is converted to a RGB value according to the monitor’s display profile (step 2).

Device Profiles Cont’d Color management systems really do only two things: They describe the color of pixels, and they change the values of pixels to keep the color consistent across different devices. The essential tools –A Reference color space that represents color as we see it. (LAB) –Device profiles, which describe a device's color behavior in terms of RGB or CMYK values –Color engines, the software that does the actual work of matching color from device to device (aka CMM – Color Management Module in computer speak). –Calibration Devices – Device profiles, unfortunately, vary for many reasons.

Color Engine Color engine Goal –Translate color information between systems –Manage color gamut differences to the satisfaction of the observer –Account for the vagaries of light and it’s Mesmerism impact If device profiles are accurate, translation is straightforward, at least for color values that are within the receiving device’s color gamut.

Color Engine Cont’d Color space conversion is what happens when the CMM translates color from one device's space to another. Conversion may require approximations in order to preserve the image's most important color qualities. Knowing how these approximations work can help you control how the photo may change-- hopefully maintaining the intended look or mood

Color Space Conversion Cont’d The CMM applies Rendering Intent to resolve the Gamut mismatch

Color Space Conversion Gamut Mismatch & Rendering Intent –The translation stage attempts to create a best match between devices-- even when seemingly incompatible. If the original device has a larger color gamut than the final device, some of the colors may be outside the final device's color space. “Out-of-gamut colors" occur with nearly every conversion and are called a gamut mismatch. –Rendering Intents are methods to resolve the mismatch

Rendering Intent Cont’ Color Conversion-Rendering IntentColor Conversion

Schematic

Monitor Calibration A properly adjusted monitor is needed before a profile can be created –Brightness –Black level –Gamma (mid-point brightness)

Monitor Calibration Cont’d Do the patches marked 0 and 10 in the grayscale appear to be the same? If they do then you need to calibrate your monitor black point. Do the patches marked 95 and 100 appear to be the same? If they do then you need to calibrate your monitor white point. If the patches have a color tint, you can correct problem by calibrating monitor gamma for each color channel individually. Stand ten feet from your monitor and examine the above figure. If the smooth patch is darker or lighter than the background then you need to calibrate monitor gamma. You can calibrate black and white points without any special software. To adjust monitor gamma, you'll need special software such as Adobe Gamma