Light and Color

1
Light and Color
2
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

3
Structure of the Human Eye

• Image taken from http//hyperphysics.phy-astr.gsu.
  edu/hbase/vision/eye.html

4
Main Parts of the Eye

• Cornea

5
Main Parts of the Eye

• Cornea
• Provides most refraction

6
Main Parts of the Eye

• Cornea
• Provides most refraction
• Reshaped in refractive surgery
• Corrects nearsightedness caused by elongation of
  the eyeball

7
Main Parts of the Eye

• Cornea
• Iris

8
Main Parts of the Eye

• Cornea
• Iris
• Opens and Closes to let in more/less light

9
Main Parts of the Eye

• Cornea
• Iris
• Opens and Closes to let in more/less light
• Hole is the pupil

10
Main Parts of the Eye

• Cornea
• Iris
• Lens

11
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Flexible - muscles adjust shape

12
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Flexible - muscles adjust shape
• Allows fine-detail focus

13
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Flexible - muscles adjust shape
• Allows fine-detail focus
• Toughens with age, leading to reading glasses
• Cataracts form here

14
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Retina

15
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Retina
• Layer of receptor cells at back of eye

16
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Retina
• Layer of receptor cells at back of eye
• Center of focus is the fovea

17
Main Parts of the Eye

• Cornea
• Iris
• Lens
• Retina
• Layer of receptor cells at back of eye
• Center of focus is the fovea
• Optic nerve collects information from retina, and
  brings to the back of the brain
• Causes a blind spot!

18
Focusing Light

• For a point in focal plane, all light emitting
  from that point goes to same point on retina

19
Focusing Light

• For a point not in focal plane, light gets spread
  across retina
• Also happens in
• nearsightedness
• Our brain is good
• at eliminating
• these signals

20
Display Screens and Focus

• For the usual (current) display systems, we
  maintain one focus plane
• Even for stereo displays
• Even if the image tries to simulate differing
  focus
• This is different than nature

21
Rods

• Distinguish brightness only
• Best response to blue-green light
• Prevalent except at fovea (more peripheral)
• About 100x more sensitive than cones
• About 100 million in retina

22
Cones

• Color response
• Centered around fovea
• About 147,000 cones/mm2 at fovea
• 2mm away from fovea 9,500 cones/mm2
• 6.3 - 6.8 million in retina

23
How We See

• Individual receptors give response
• Vision is limited by density of cells in part of
  brain
• High detail, good color at center of vision
• Peripheral vision can see dimmer light, but
  mainly black white, and low resolution

24
Vision in the Brain

• Signals are carried by optic nerve to brain
• Brain processes to reconstruct image
• Best understood part of brain function, but still
  many ill-understood parts
• Many aspects of vision are hard-wired
• Can lead to optical effects with significant
  graphics impact
• Mach banding.
• Filling in of blind spot

25
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

26
Intensity and Luminance

• Intensity/Luminance How much light energy there
  is
• The amount of energy carried by photons

27
Intensity and Luminance

• Intensity/Luminance How much light energy there
  is
• The amount of energy carried by photons
• Brightness the perceived intensity
• Eye does not respond to equal intensity changes
  equally
• Eye notices the ratio of intensities

28
Brightness Levels

• Intensity changes of 1-gt2, 2-gt4, 4-gt8 appear the
  same
• Example 3-way lightbulb
• 50-gt100 seems like bigger change than 100 -gt 150
• Display devices might limit the number of
  discrete intensity levels available

29
Brightness in Display Devices

• Assume
• The maximum intensity of a display is 1.0
• The minimum is I0
• It can display n1 intensity levels
• Then, to get equal brightness increments, it
  should display levels
• I0, rI0, r2I0, , rnI01.0

30
Brightness Levels

• Human eye generally can notice rgt1.01
• So, to have a smooth display, we need to make
  sure that rlt1.01
• i.e. we need enough levels of display
• For a given display, we need
• 1.01nI01.0
• 1.01n 1.0/I0
• n log 1.01 - log I0
• n -log I0 / log 1.01
• n -log1.01I0

31
Dynamic Range

• 1/I0 is called dynamic range
• The ratio of maximum to minimum intensity
  (remember, we set 1.0 max)
• Varies by display device
• This is the maximum a device can possibly display
  vs. the minimum it can display.

32
Dynamic Range

• 1/I0 is called dynamic range
• The ratio of maximum to minimum intensity
  (remember, we set 1.0 max)
• Varies by display device
• This is the maximum a device can possibly display
  vs. the minimum it can display.
• Contrast the maximum vs. minimum it can display
  at the same time.
• i.e. for one image on screen, maximum vs.
  minimum.

33
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

34
Limited Display Levels

• We cant always get a continuous range of display
  levels
• Printing either ink is there or not there
• We can adjust amount of ink (i.e. how much space
  it takes), but not its intensity
• Other display might limit the number of levels
  e.g. 256 levels of intensity.
• We need ways to mimic continuous colors with
  discrete levels

35
Example
36
Example
37
Halftoning/Dithering

• Idea Eyes integrate over an area
• All light hitting one receptor cell is combined.
• Eye only cares about the integrated information
  from an entire area
• So, we can get varying intensity by filling in
  fractions of areas

vs.
38
Halftoning

• Subdivide image into blocks of pixels.
• You will lose resolution!
• e.g. a 100x100 region divided into 4x4 blocks of
  pixels can only display a 25x25 image.
• The number of intensity levels is related to the
  number of pixels in a block
• 2x2 5 intensity levels
• 3x3 10 intensity levels
• nxn n21 intensity levels

39
Example 2x2 block

• Level 0 Intensities 0.0 0.2
• Level 1 Intensities 0.2 0.4
• Level 2 Intensities 0.4 0.6
• Level 3 Intensities 0.6 0.8
• Level 4 Intensities 0.8 1.0

40
Example Image
41
2x2 Halftone Example
42
2x2 Halftone Example
43
3x3 Halftone Example
44
Halftoning Patterns

• The pattern you use to fill makes a difference.
• Want a random pattern, so that artificial
  artifacts dont appear
• Brain is very good at recognizing some things,
  like lines

45
Example 3x3 block

• Bad pattern
• Better pattern

46
3x3 Bad Halftone Example
47
3x3 Good Halftone Example
48
Dithering

• Halftoning loses resolution this is bad.
• Dithering
• Keep same resolution
• Change halftoning pattern into a
  probability/threshold function (dither pattern)
• Overlay dither pattern on entire image
• Fill in a pixel iff it is of higher intensity
  than the dither value

49
Dither Pattern Example

• Intensities 0.0 0.2
• Intensities 0.2 0.4
• Intensities 0.4 0.6
• Intensities 0.6 0.8
• Intensities 0.8 1.0

Halftoning Patterns
50
Dither Pattern Example

• Intensities 0.0 0.2
• Intensities 0.2 0.4
• Intensities 0.4 0.6
• Intensities 0.6 0.8
• Intensities 0.8 1.0

Cells are filled in only when intensity is
larger than the given value
51
Dither Pattern Example
Overlay dither pattern
52
Dither Pattern Example
Fill those cells larger than dither value
53
Dither Pattern Example
Fill those cells larger than dither value
54
Dither Pattern Example
Fill those cells larger than dither value
55
Dither Pattern Example
Fill those cells larger than dither value
56
Dither Pattern Example
Fill those cells larger than dither value
57
Dither Pattern Example
Repeat for rest of image
58
3x3 Halftone Example
59
3x3 Dither Example
60
Error Diffusion

• Another way to set levels without changing
  resolution
• Assume pixels being visited in some order
• Left to right, top to bottom
• Roundoff error (from filling/not filling) gets
  diffused to adjacent pixels not visited yet
• Can be combined with halftoning/dithering

61
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Given
62
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 50
63
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 50 Error of 16
64
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 50 Error of 16
65
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

66
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 100
67
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 100 Error of -16
68
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

Round to 100 Error of -16
69
Error Diffusion

• Pattern
• Example Assume we can display levels in
  increments of 50.

70
3x3 Dither Example
71
Error Diffusion Example
72
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

73
Light

• Light is carried by photons, traveling with
  different wavelengths/frequencies
• cln
• Speed of light c (assume constant)
• Wavelength l
• Frequency n
• So, Wavelength Frequency are interchangable,
  and inverse of each other

74
Visible Light

• Image taken from http//www.andor.com/image_lib/lo
  res/introduction/introduction20(light)/intlight2
  0120small.jpg

75
Visible Light

• The response of the cells in our eye let us see
  from 400nm (violet) to 700nm (red).
• If all light arriving is one wavelength, we see
  it as one color.

76
Visible Light

• The response of the cells in our eye let us see
  from 400nm (violet) to 700nm (red).
• If all light arriving is one wavelength, we see
  it as one color.
• But, Light usually comes in as a spectrum
  different intensities at all the various
  wavelengths.

Images taken from http//www.newport.com/Informati
on-on-Oriel-Spectral-Irradiance-Data/383232/1033/c
atalog.aspx
77
Seeing Color

• So, how is it that we look at a spectrum of
  light, and see it as a single color?

78
Tristimulus Theory

• There are 3 kinds of cones in the eye that
  respond differently to different wavelengths of
  light.

79
Tristimulus Theory

• There are 3 kinds of cones in the eye that
  respond differently to different wavelengths of
  light.
• Anything that stimulates these cones in the same
  way appears as the same color.
• This is fundamental to our ability to reproduce
  different colors!
• A monitor can stimulate the cones to make it
  appear that a particular color is being generated.

80
Response of Cones

• 3 Cones, Rods respond to light differently

Image taken from http//www.unm.edu/toolson/human
_cone_response.htm
81
Receptor Response

• Though cones often called red, green, blue, the
  peak responses are actually in the yellow,
  yellow-green, and violet.
• Altogether, overall response is Gaussian-like,
  centered on yellow/green
• Sun and plants

Image taken from http//www.unm.edu/toolson/human
_cone_response.htm
82
Tristimulus

• Since 3 different cones, the space of colors is
  3-dimensional.
• We need a way to describe color within this 3
  dimensional space.
• We want something that will let us describe any
  visible color

83
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

84
The CIE XYZ system

• CIE Comission Internationale de lEclairage
• International Commission on Illumination
• Sets international standards related to light
• Defined the XYZ color system as an international
  standard in 1931
• X, Y, and Z are three Primary colors. All
  visible colors can be defined as a combination of
  these three colors.
• Defines the 3 dimensional color space

85
Color Matching Functions

• Given an input spectrum, , we want to find
  the X, Y, Z coordinates for that color.
• Color matching functions, , , and
• tell how to
  weight
• the spectrum
  when
• integrating

Image taken from http//upload.wikimedia.org/wikip
edia/commons/8/87/CIE1931_XYZCMF.png
86
XYZ space

• The visible colors form a cone in XYZ space.
• For visible colors, X, Y, Z are all positive.
• But, X, Y, and Z themselves are not visible
  colors!

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
87
Luminance and Chromaticity

• The intensity (luminance) is just XYZ.
• Scaling X, Y, Z just increases intensity.
• We can separate this from the remaining part,
  chromaticity.
• Color Luminance Chromaticity
• Chromaticity is 2D, Luminance is 1D
• To help us understand chromaticity, well fix
  intensity to the XYZ1 plane.

88
Chromaticity Diagram

• Project the XYZ1 slice along the Z-axis
• Chromaticity is given by the x, y coordinates

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
89
White Point

• White at the center of the diagram.

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
90
Spectral Colors

• Visible Spectrum along outside curve

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
91
Saturation

• As you move on line from white to edge, you
  increase the saturation of that color.
• Royal blue, red high saturation
• Carolina blue, pink low saturation

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
92
Hue

• Hue is the direction from white.
• Combined with saturation, it gives another way to
  describe color
• Also called dominant wavelength

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
93
Non-Spectral Colors

• Non-spectral colors do not correspond to any
  wavelength of light.
• i.e. not seen in rainbow
• e.g. maroon, purple, magenta

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
94
Combining Two Colors

• If we have two colors, A and B, by varying the
  relative intensity, we can generate any color on
  the line between A and B.

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
95
Complementary Colors

• Complementary colors are those that will sum to
  white.
• That is, white is halfway between them.

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
96
Combining Three Colors

• If we have three colors, A, B, and C, by varying
  the relative intensity, we can generate any color
  in the triangle between them.

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
97
Gamut

• Display devices generally have 3 colors (a few
  have more).
• e.g. RGB in monitor
• The display can therefore display any color
  created from a combination of those 3.
• This range of displayable colors is called the
  gamut of the device.

98
Differing Gamuts

• Different devices have different gamuts
• e.g. differing phosphors
• So, RGB on one monitor is not the same as RGB on
  another

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
99
Device Gamuts

• For monitors, typically have colors in the Red,
  Green, Blue areas
• Helps cover lots of visible spectrum
• But, not all (in fact, nowhere close to all) of
  the visible spectrum is ever represented
• Since all 3 colors are visible, cant possibly
  encompass full visible spectrum!

100
Gamuts

• Red typical monitor gamut
• Blue maximum gamut with 3 phosphors

Image taken from http//fourier.eng.hmc.edu/e180/h
andouts/color1/node27.html
101
Topics

• The Human Visual System
• Displaying Intensity and Luminance
• Display Using Fixed Intensities
• Understanding Color
• Display of Color
• Color Models

102
Color Models

• CIEs XYZ system is a standard, but not very
  intuitive.
• As we saw with saturation and hue, theres more
  than one way to specify a color.
• A variety of color models have been developed to
  help with some specifications.

103
RGB

• Red, Green, Blue
• Common specifications for most monitors
• Tells how much intensity to use for pixels
• Note Not standard RGB means different things
  for different monitors
• Generally used in an additive system
• Each adds additional light (e.g. phosphor)
• Combine all three colors to get white

104
CMY

• Cyan, Magenta, Yellow
• Commonly used in printing
• Generally used in a subtractive system
• Each removes color from reflected light
• Combine all three colors to get black
• Conceptually, C M Y 1 1 1 R G B
• Complimentary colors to RGB

105
CMYK

• Cyan, Magenta, Yellow, Black
• Comes from printing process since CMY combine
  to form black, can replace equal amounts of CMY
  with Black, saving ink.
• K min(C, M, Y)
• C C-K
• M M-K
• Y Y-K

106
YIQ / YUV

• NTSC, PAL standards for broadcast TV
• Backward compatible to Black and White TV
• Y is luminance only part picked up by Black and
  White Televisions
• Y is given most bandwith in signal
• I, Q channels (or U,V) contain chromaticity
  information

107
HSV

• Hue, Saturation, Value
• Used as a user-friendly way to specify color.
• Hue angle around cone
• Saturation how far from center
• Value (luminance) how high up cone (black at
  bottom, white at top center).

Image taken from http//www.mandelbrot-dazibao.com
/HSV/HSV.htm
108
HLS

• Hue, Lightness, Saturation
• A variation on HSV, but with a double cone
• Lightness black at base (0), white at top (1)

Image taken from http//en.wikipedia.org/wiki/Imag
eColor_cones.png
109
Lab and Luv

• Perceptually-based color spaces (CIE standards)
• Idea want the distance between colors in the
  color space to correspond to intuitive notion of
  how similar colors are
• Not perfect, but much better than XYZ or RGB
  color spaces.

110
Representing Color

• Generally, store 3 color channels in equal bits
• Not necessary, though, e.g. YIQ
• Can sometimes get better mapping of color space
  for an application by adjusting bits
• e.g. 10 bits R, 8 bits G, 6 bits B
• Color indexing give each color a numerical
  identifier, then use that as reference
• Good for specifying with a limited palette
• Note you can use dithering/halftoning with color
  channels, similar to how you would for achromatic
  light.

111
(No Transcript)
112
The Retina

• Retina is made up of many receptor cells
• Two main types, rods and cones
• About 6.3-6.8 million cones
• Highest concentration of cones is at the fovea
  (center of focus)
• About 147,000 cones/mm2
• 2mm away from fovea 9,500 cones/mm2

113
Rods and Cones

• Rods
• Distinguish brightness only
• Best response to blue-green light
• Prevalent except at fovea (more peripheral)
• About 100x more sensitive than cones
• About 100 million in retina
• Cones
• Color response
• Centered around fovea
• About 147,000 cones/mm2 at fovea
• 2mm away from fovea 9,500 cones/mm2
• 6.3 - 6.8 million in retina

114
Gamma Correction

• A correction term used to relate the intensity of
  light output to the the voltage of the CRT
  electron gun (i.e. between the cathode and the
  grid (anode)).
• Not just a way to adjust game brightness!
• I k Ng
• I intensity, N of electrons
• k, g are device-specific terms
• Typically, g 2.0 to 2.5 for most CRTs

115
Gamma and non-CRT Displays

• Gamma is meant to model CRTs only
• Other displays (e.g. LCD) may have very different
  response curves between intensity and value sent
• They do not match the gamma curve
• Often manufacturers adjust responses to try to
  mimic CRT behavior
• Rarely is any devices response curve exactly
  what is desired/modeled
• This can get much more complicated
• Major effort just to compensate for gamma

116
Dynamic Range and Contrast of Various Display
Mediums