Transcript Color Management 12/07/06 - Rochester Computer Socitey Inc

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, lightindependent, 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
3-D CIE LAB space
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.
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%
Commercial 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
Canon I9900 75%
Consumer Ink Jet
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 devicespecific 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 Intent
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