Achromatic light

1
Color in Computer Graphics

• Introduction
• Achromatic light
• Chromatic color
• Color models for raster graphics
• Reproducing color
• Using color in computer graphics

2
Introduction
Color is an immensely complex subject

• Physics
• Physiology
• Psychology
• Art
• Graphic design

Many theories, measurement techniques, and
standards for colors. No one theory of human
color perception universally accepted.
3
Introduction

• Color of object depends not only on object
  itself
• Light source (color / direction)
• Object material (reflective, transmits light)
• Color of surrounding area
• Human visual system (the eye/brain mechanism)

4
Achromatic Light

• Seen on black and white TV or display monitors
• No sensations that we associate with colors.
• Quantity of light is the only attribute.

• Quantity of light
• Intensity / luminance Physics
• Brightness Psychology

Useful to associate a scalar quantity with
different intensity levels Black
Grays White 0-------------------
-----------------------------------------1
5
Selecting Intensities

• How do we divide our range from 0 to 1 to be able
  to
• represent 256 intensity levels ?
• 128 in 0, 0.1 and 128 in 0.9, 10
• Visible gap from 0.1 to 0.9
• Want predictability
• Even distribution ?
• Ignores important characteristic of human eye.
• Eye is sensitive to ratios of intensity levels
  rather
• then absolute values of intensity.
• Perceive difference between 0.10 and 0.11 to be
• the same as difference between 0.50 and 0.55
• Studies have shown that the eye responds in a
  logarithmic way.

6
Selecting Intensities

• Logarithmic distribution Each intensity level is
  r times higher than previous intensity level

I0 I0 I1 rI0 I2 rI1 r2I0 ... I255
r255I0 1

• Rearrange to find r

(In general for n levels r (1/I0)1/n-1)
r (1/I0)1/255
The quantity 1/I0 is called the Dynamic range of
a device i.e. ratio of maximum to minimum
intensities.

• Use r to find any intensity value j for 0, 255
• Ij rjI0

7
Selecting Intensities
n 4 I0 1/8

• Example

gt r (1/I0)1/n-1) 2
gt Intensity values are 1/8, 1/4, 1/2, 1

• Typical CRT I0 anywhere from 1/200 to 1/40 of
  maximum intensity gt I0 between .005 and .025
• I0 not zero because of light reflection off CRT
  phosphors.
• Exact value for a specific CRT can be measured
  with a photometer.

8
Displaying Intensities

• How many intensities are enough to achieve a
  continuous tone image from black to white ?
• Experiments have shown r 1.01or less. Below
  this ratio the human eye cannot distinguish
  between Ij and Ij1.
• Solve for n

n log1.01(1/I0)
The quantity 1/I0 is called the Dynamic range of
a device i.e. ratio of maximum to minimum
intensities.
9
Display Media

• Dynamic range (1/I0) and theoretical number of
  required
• intensities n log 1.01(1/I0) for several
  display media (ink
• bleeding, random noise considerably decreases n
  in
• practice)

10
Displaying Intensities

• CRT Monitors
• 3 guns firing electrons at slightly different
  angles to illuminate phosphors coating the inside
  of the tube.
• The guns follow the signals it receives from
  the graphics controller.
• The phosphors light up when hit with electrons,
  mixing red, green, and blue to create the colors
  you see on the screen.
• The point where one set of adjacent red, green,
  and blue phosphors meet constitutes a pixel
  (short for "picture element"),
• Because the phosphors that make up a pixel light
  up only briefly, they need to be constantly
  refreshed, so the beam continually seeps the
  inside of the tube.

11
Displaying Intensities

• Intensity of light output by a phosphor is given
  by
• I kN
• N number of electrons in beam, proportional to
  grid voltage.
• k, are constants
• Different phosphors respond differently to equal
  amounts of electrons.
• I0, k and depend on the CRT being used. So
  different
• CRTs will display differently.
• In practice a lookup table can be used (based on
  actual
• measurement of intensities) to generate the same
  intensities
• on different monitors. Called Gamma Correction

is typically in the range of 2.2 to 2.5
12
Displaying Intensities

• Gamma (?) is a measure of the non-linearities of
  a CRT
• Term often used incorrectly to refer to
  non-linearity of image data
• Example PC monitors have a gamma of roughly 1.8,
  while Mac monitors have a gamma of 2.2, so Mac
  images appear dark on PCs
• Problem in graphics
• Need to maintain color consistency across
  different platforms and hardware devices
  (monitor, printer, etc)
• Even the same type/brand of monitors change gamma
  value over time
• Proper design and use of color software

13
Chromatic Color

• Visual sensations much richer than achromatic
  light.
• Typically involve 3 quantities
• Hue distinguishes among colors such as red,
  green, purple, and yellow
• Saturation refers to how pure the color is, how
  far from gray of equal intensity
• Red Is highly saturated pink is relatively
  unsaturated
• Royal blue is highly saturated sky blue is
  relatively unsaturated
• Pastels are unsaturated
• Lightness embodies the achromatic notion of
  perceived intensity of a reflecting object
• Brightness is used instead of lightness to refer
  to the perceived intensity of a self-luminous
  (I.e., emitting rather than reflecting light)
  object, such as a light bulb, the sun, or a CRT

14
Specifying (Naming) Color

• Specifying and measuring colors is necessary if
  we are to use them precisely in computer
  graphics
• Visually comparing a sample of unknown color
  against a sample of standard colors (reflected
  light). Must be done under standard light source.
• Munsell color-order system (published standard
  colors)
• Hue, Value (lightness), Chroma (saturation)
• Named colors
• Order shows equal (perceived) distance in color
  space as judged by numerous observers.
• PANTONE Matching System in printing industry

15
The Munsell System
Munsell Value
Munsell Chroma (saturation)
Munsell Hue
Munsell Color Space
16
Specifying (Naming) Color

• Artists specify color as tint, shade, tone of
  strongly saturated or pure pigments.
• A tint results from adding a white pigment to a
  pure pigmentdecreasing saturation
• A shade results from adding a black pigment to a
  pure pigmentdecreasing lightness
• A tone results from adding both white and black
  pigments to a pure pigment
• NOTE Same hue, varying saturation and lightness.
• Ostwald color-order system is based on this model

17
Psychophysics

• Comparison of tint, shade, and tone are
  subjective, perceptually-oriented concepts
  depend on observers judgment, lighting, sample
  size, surrounding color, overall lightness of
  environment
• Need a more quantitative way to specify colors
• Colorimetry is quantitative, physics-oriented
  approach to describing and measuring color (using
  spectroradiometer, colorimeter, etc.)

18
Psychophysics
19
Psychophysics
Energy Density
Typical spectral energy distribution
Perceptual term
Colorimetry term Hue Dominant
wavelength Saturation Excitation
purity Lightness (reflecting objects)
Luminance Brightness (self-luminous objects)
Luminance
20
Energy Distribution and Metamers

• The spectral distribution can be described by the
  triple (dominant wavelength, excitation purity,
  luminance)
• Many spectral distributions produce the same
  color
• Two spectral energy distributions that are
  perceived as the same color are called metamers

21
How the eye works

• Retina light sensing structure of the eye.
• Contains 2 types of cells
• Rods
• Cones
• Rods handle vision in low light
• Cones handle color vision and detail.
• When light contacts these two types of cells, a
  series of complex chemical reactions occurs.
• These reactions generate electrical impulses in
  the optic nerve which sends it to the brain.
• The retina contains 100 million rods and 7
  million cones.

22
How the eye works

• Eye contains three kinds of color-sensitive
  pigments
• Red-sensitive pigment
• Green-sensitive pigment
• Blue-sensitive pigment
• Each cone cell has one of these pigments so that
  it is sensitive to that color. The human eye can
  sense almost any gradation of color when red,
  green and blue are mixed. (Called the
  Tristimulus Theory)

Spectral response functions of 3 types of cones
in human retina.
23
Color Matching

• Tristimulus theory leads to notion of matching
  all visible colors with combinations of red,
  green, and blue mono-spectral primaries it
  almost works
• Negative value gt cannot match, must subtract,
  Note that mixing positive amounts of R, G, B
  primaries provides large color gamut, e.g., CRT.
  But CRT cant show all colors!

24
CIE Chromaticity Diagram

• Commission Internationale de lÉclairage (CIE)
• Defined X, Y, and Z primaries to replace red,
  green and blue primaries
• x? y?, and z?, color-matching functions (not
  spectral distributions) for these primaries

25
XYZ Space Showing an RGB
Gamut

• The color gamut for a typical color monitor with
  the XYZ color
• space. The range of colors which can be
  displayed on the monitor
• is clearly smaller than all colors visible in
  XYZ space.

All colors
Displayable colors
26
CIE Space

• Several views of the X Y Z 1 plane of CIE
  space. Left the
• plane embedded in CIE space. Top right a view
  perpendicular to
• the plane. Bottom right the projection onto
  the (X, Y) plane (that
• is, the Z 0 plane), which is the chromaticity
  diagram

27
CIE Chromaticity Diagram

• CIE chromaticity diagram is the projection onto
  the xy plane of the x y z 1 plane
• Luminance is factored out
• All perceivable colors with same chromacity but
  different luminances map into same point
• 100 spectrally pure colors are on curved part

28
CIE Chromaticity Diagram

• Uses of CIE Chromaticity diagram
• Allows us to measure dominant wavelength and
  excitation purity of any color by matching the
  color with a mixture of the 3 CIE primaries
• Define color mixing
• Define and compare color gamuts
• Gamut is set of colors visible via particular
  medium

29
CIE Chromaticity Diagram

• When two colors added, new color lies on straight
  line connecting two colors A tC (1 t)B
• Ratio AC/BC is excitation purity of A
• Complementary colors can be mixed to produce
  white light (a decidedly non-spectral color!)
  white can thus be produced by an approximately
  constant spectral distribution as well as by only
  two complimentary spectral colors, e.g., D and E

Matched color at A
30
Color Gamuts

• Any two colors, I and J, can be added to produce
  any color along their connecting line by varying
  relative amounts of two colors
• Third color K can be used with various mixes of I
  and J to produce a gamut of all colors in
  triangle IJK, again by varying relative amounts
• Shape of diagram shows why visible red, green and
  blue cannot be additively mixed to match all
  colors no triangle whose vertices are within the
  visible area can completely cover visible area
  (e.g., purple and magenta)
• Matching of all visible colors requires negative
  amounts of primaries for some

31
Color Gamuts

• Smallness of print gamut with respect to color
  monitor gamut faithful reproduction by
  printing must use reduced gamut of colors on
  monitor

32
Color Models for Raster Graphics
(1/2)

• Purpose specify colors in some gamut
• Since gamut is a subset of all visible
  chromaticities, model does not contain all
  visible colors
• 3D color coordinate system subset containing all
  colors within a gamut
• Means to convert to other model(s)

33
Color Models for Raster Graphics
(2/2)

• Hardware-oriented models not intuitive do not
  relate to concepts of hue, saturation, brightness
• RGB, used with color CRT monitors\
• YIQ, the broadcast TV color system
• CMY (cyan, magenta, yellow) for color printing
• CMYK (cyan, magenta, yellow, black) for color
  printing
• User-oriented models
• HSV (hue, saturation, value) also called HSB
  (hue, saturation, brightness)
• HLS (hue, whiteness, blackness)
• The Munsell system
• CIE LUV
• HVC (Tektronix proprietary)

34
The RGB Color Model (1/3)

• RGB primaries are additive
• The RGB cube. (Grays are on the dotted main
  diagonal)
• Main diagonal gray levels black is (0, 0,
  0) white is (1, 1, 1)
• RGB color gamut defined by CRT phosphor
  chromaticities
• Differs form one CRT to another

35
The RGB Color Model (2/3)

• Conversion from one RGB gamut to another
• Convert one to XYZ, then convert from XYZ to
  another
• Form of each transformation
• Where xr, xg, and xb are the weights applied to
  the monitors RGB colors to find x, and so on
• M is the 3 x 3 matrix of color-matching
  coefficients
• Let M1 and M2 be matrices to convert from each of
  the two monitors gamuts to CIE
• M2-1 M1 converts form RGB of monitor 1 to RGB of
  monitor 2

36
The RGB Color Model (3/3)

• But what if
• C1 is in the gamut of monitor 1 but is not in the
  gamut of monitor 2, I.e., is outside the unit
  cube and hence is not displayable?
• Solution 1 clamp RGB at 0 and 1
• Simple, but distorts color relations
• Solution 2 compress gamut on monitor 1 by
  scaling all colors from monitor 1 toward center
  of gamut 1
• Ensure that all displayed colors on monitor 1 map
  onto monitor 2

37
The CMY(K) Color Model (1/2)

• Cyan, magenta, and yellow are complements of red,
  green , and blue
• Subtractive primaries colors are specified by
  what is removed or subtracted from white light,
  rather than by what is added to blackness
• Cartesian coordinate system
• Subset is unit cube
• White is at origin, black at (1, 1, 1)
• Mixing Subtractive primaries (C,M,Y)

38
The CMY(K) Color Model (2/2)

• Color printing presses, some color printers use
  CMYK (Kblack)
• K used instead of equal amounts of CMY
• Called undercolor removal
• Richer black
• Less ink deposited on paper dries more quickly

39
The YIQ Color Model

• Recoding for RGB for transmission efficiency and
  downward compatibility with B/W broadcast TV
  used for NTSC (National Television Standards
  Committee (or never the same color))
• Y is luminance same as CIE Y primary
• I and Q encode chromaticity
• First row relative importance of RGB in
  brightness (Note low B)
• YIQ exploits properties of our visual system to
  maximize information transmitted
• More sensitive to changes in luminance than
  changes to hue or saturation. gt More bits to
  represent Y then I or Q
• 4 MHz for the Y channel
• 1.5 MHz for I (small images need only 1 color
  dimension
• 0.6 MHz for the Q channel

40
The HSV Color Model (1/2)

• Hue, saturation, value (Hue, saturation,
  brightness)
• Hexcone subset of cylindrical (polar) coordinate
  system
• Single hexcone HSV color model. (The V 1
  plane contains the RGB models R 1, G 1, B
  1, in the regions shown)
• Has intuitive appeal of the artists tint, shade,
  and tone model

41
The HSV Color Model (2/2)

• Colors on V 1 plane are not equally bright
• Complementary colors 180 opposite
• Saturation measured relative to color gamut
  represented by model which is subset of
  chromaticity diagram
• Therefore, 100 S 100 excitation purity
• Top of HSV hexcone is projection seen by looking
  along principal diagonal of RGB color
• RGB color cube viewed along the principal
  diagonal
• Code for RGB HSV on Page 592, 593
• Note linear path RGB lt gt linear path in HSV!

42
The HLS color Model

• Hue, lightness, saturation
• Double-hexcone subset
• Maximally saturated hues are at S 1, L 0.5
• Less attractive for sliders or dials
• Neither V nor L correspond to Y in YIQ!

43
Problems with Standard Color
Systems

• They are perceptually non-uniform
• Move through color space from color C1 to a new
  color C1? through a distance ?C
  C1? C1 ?C
• Move through the same distance ?C, starting from
  a different color C2
  C2? C2 ?C
• The change in color in both cases is
  mathematically equal, but is not perceived as
  equal
• Moving a slider almost always causes a perceptual
  change in the other two values, which is not
  reflected by changes in those sliders. Thus,
  changing hue frequently will affect saturation
  and value
• Ideally want a perceptually uniform space
  two colors that are equally distant
  are perceived as equally distant, and changing
  one value does not perceptually alter the other
  two
• Historically, the first perceptually-uniform
  color space was the Munsell system

44
CIE LUV

• 1976 CIE LUV provides a compromise between a
  mathematically described space and a perceptually
  uniform color space
• Much more perceptually uniform than the 1931 CIE
  system
• Still described mathematically
• Given white (Xn, Yn, Zn)
• These transformations cause regions of colors
  perceived as identical to be of the same size

45
Tektronix HVC

• Hue, value, chroma
• Modification of CIE LUV perceptually uniform
  color space
• Color space details are proprietary, but CIE LUV
  is computationally simple

46
Color Model Pros and Cons (1/2)

• RGB
• Cartesian coordinate system
• linear
• hardware-based (easy to transform to video)
• tristimulus-based
• - hard to use to pick and name colors
• - doesnt cover gamut of perceivable colors
• - non-uniform equal geometric distance gt
  unequal
• perceptual distance
• CIE
• covers gamut of perceived colors
• based on human perception (matching
  experiments)
• linear
• contains all other spaces
• - non-uniform (but two new variations, CIE Lab
  and CIE
• LUV, are closer to Munsell, which is
  uniform)
• - xy-plot of chromaticity horseshoe diagram
  doesnt show
• luminance

47
Color Model Pros and Cons (2/2)

• HSV
• easy to convert to RGB
• easy to specify colors (artists Model)
• - non-linear
• - doesnt cover gamut of perceivable colors
• - non-uniform

48
Interactive Specification of Color
(1/2)

• English-language names
• Ambiguous and subjective
• Numeric coordinates in color space with slide
  dials
• Two types of sliders for setting color
• - Good if user understands how each dimension
  affects color

49
Interactive Specification of Color
(2/2)

• Interact with visual representation of the color
  space
• A convenient way to specify colors in HSV space
• Important for user to see actual display with new
  color
• Beware of surround effect!

50
The gray patches on the blue and yellow
backgrounds are physically identical. But they
dont look that way to begin with, there is a
difference in perceived brightness the patch on
the blue looks brighter than the one on the
yellow, a result of brightness contrast. There
is also a difference in perceived hue, for the
patch on the blue looks somewhat yellowish, while
that on the yellow looks bluish. This is color
contrast, a demonstration that hues tend to
induce their antagonists in neighboring areas.
51
Interpolating in Color Space (1/2)

• Interpolation needed for
• Gouraud shading
• Antialiasing
• Blending images together in a fade-in, fade-out
  sequence
• Results depend on the color model used
• RGB, CMY, YIQ, CIE are related by affine
  transformations, hence straight line (I.e.,
  interpolation paths) are maintained during
  mapping
• Not so for HSV, HLS, HVC.

52
Interpolating in Color Space (2/2)

• For Gouraud shading, use any of the models
  because interpolants generally so close together
  that interpolation paths are close together
• For blending two images, as in fade-in fade-out
  sequence or for antialiasing, colors may be quite
  distant
• Use additive model, such as RGB
• If interpolating between two colors of fixed hue
  (or saturation), maintain fixed hue (saturation)
  for all interpolated colors by HSV or HLS
• Note fixed-saturation interpolation in HSV or HLS
  is not seen as having exactly fixed saturation by
  viewer!

53
Using Color in Computer
Graphics

• Aesthetic uses
• Establish a tone or mood
• Promote realism
• Highlight
• Code numeric quantities
• Temperature across the U.S.
• People use color even in cases when there is no
  quantitative evidence that it improves
  understanding in what they are trying to
  communicate
• Based on likes and dislikes

54
Using Color in Computer
Graphics Functionality

• Careless use of color perilous
• Decorative use of color subservient to functional
  use
• Test with real users
• Provide best judgment defaults
• Allow user to override defaults
• Design first for a monochrome display (color use
  is redundant in monochrome displays and for
  color-blind users)
• Conservative is better !

55
Using Color in Computer
Graphics Approach

• Color harmony
• Select colors according to some method, typically
  by traversing a smooth path in a color model
• Restrict colors to planes or hexcones in a color
  space
• Space colors at equal perceptual distances
• Light-dark contrast more important than hue
  contrast
• Specifics
• If a chart contains just a few colors, the
  complement of one of the colors should be used as
  the background
• Use neutral (gray) background for an image with
  many colors
• Separate non-harmonious colors by thin black
  border
• Coding
• Use small number of colors
• Show reference scale
• Color can carry unintended meanings
• Bright, saturated colors stand out (may give
  unintended emphasis)
• Display elements of same color may incorrectly be
  associated by user

56
Using Color in Computer Graphics
Physiological Rules (1/2)

• Eye is more sensitive to spatial variation
• Fine detail should vary from the background not
  just in chromaticity, but in brightness
• For color-blind users, avoid reds and greens with
  low saturation and luminance
• Color of small objects less than 20-40 minutes of
  arc are not distinguishable

Blue
Yellow
57
Using Color in Computer Graphics
Physiological Rules (2/2)

• Difficult to perceive color when used with small
  objects dont use color coding for them
• Perceived color of object is affected by color of
  surrounding area
• Strongly saturated colors produce after images
• Color affects perceived size
• Red seen as larger than green
• Colors refract differently through our lens
  appear at different depths
• Red (closer) vs blue (farther) strongest effect
• Apply color conservatively, not gratuitously --
  color-it-is as bad as font-it-is

58
Negative Afterimage

• Stare at the center of the figure for about a
  minute or two, and then look at a blank white
  screen or a white piece of paper
• Blink once or twice the negative afterimage will
  appear within a few seconds showing the rose in
  its correct colors (red petals and green
  leaves)