Lecture 21 Color - Massachusetts Institute of...
Transcript of Lecture 21 Color - Massachusetts Institute of...
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6.869/6.819 Advances in Computer Vision Fall 2019Bill Freeman, Antonio Torralba, Phillip Isola
Lecture 21Color
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Why does a visual system need color?
http://www.hobbylinc.com/gr/pll/pll5019.jpg
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• To tell what food is edible. • To distinguish material changes from shading
changes. • To group parts of one object together in a scene. • To find people’s skin. • Check whether a person’s appearance looks
normal/healthy.
Why does a visual system need color? (an incomplete list…)
http://www.pouted.com/know-10-points-information-unicorn/sick-child/
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Lecture outline
• Color physics. • Color perception.
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Lecture outline
• Color physics. • Color perception.
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color
www.popularpersons.org
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Spectral colors
http://hyperphysics.phy-astr.gsu.edu/hbase/vision/specol.html#c2
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Color names for cartoon spectra
400 500 600 700 nm
400 500 600 700 nm
400 500 600 700 nm
red
gree
nbl
ue
400 500 600 700 nm
cyan
mag
enta
yello
w
400 500 600 700 nm
400 500 600 700 nm
min
us
red
min
us
gree
nm
inus
bl
ue
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Additive color mixing
400 500 600 700 nm
400 500 600 700 nm
red
gree
n
Red and green make…
400 500 600 700 nm
yello
w
Yellow!
When colors combine by adding the color spectra. Example color displays that follow this mixing rule: tiny display dots on a monitor screen, multiple projectors aimed at a screen.
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Subtractive color mixingWhen colors combine by multiplying the color spectra. Examples that follow this mixing rule: most photographic films, paint, cascaded optical filters, crayons, light reflecting off a diffuse surface.
400 500 600 700 nm
cyan
yello
w
400 500 600 700 nm
Cyan and yellow (in crayons, called “blue” and yellow) make…
400 500 600 700 nmGreen!gr
een
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Horn, 1986
The interaction of light with
surfaces
Spectral radiance: power in a specified direction, per unit area, per unit solid angle, per unit wavelength
Spectral irradiance: incident power per unit area, per unit wavelength
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Simplified rendering models: BRDF reflectance as function of
wavelength
For diffuse reflections, we replace the BRDF calculation with a wavelength-by-wavelength scalar multiplication
.* =
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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Spectral albedoes for several different leaves, with color names attached. Notice that different colours typically have different spectral albedo, but that different spectral albedoes may result in the same perceived color (compare the two whites). Spectral albedoes are typically quite smooth functions. Measurements by E.Koivisto.
Forsyth, 2002
Some reflectance spectra
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.* =
Simplified rendering models: transmittance
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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Overhead projector demo
Subtractive color mixing
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Lecture outline
• Color physics. • Color perception.
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What’s the machinery in the eye?
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Eye Photoreceptor responses
(Where do you think the light comes in?)
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Human Photoreceptors
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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Human eye photoreceptor spectral sensitivities
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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L, M, and S cone receptor types colored as R, G, B
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What are some color artifacts we might expect our visual system to experience, based on this way of
measuring the light spectra falling on our eye?
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Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
2-d depiction of the 3-d subspace of sensor responses
3-d depiction of the high-dimensional space of all possible power spectra
A property of our visual system: these two spectra look the same
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Two spectra, t and s, perceptually match when
where Ceye are the cone response curves.
Color metamerism: different spectra looking the same color
Ceye Ceye
Graphically,
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Evidence of spatially offset color sampling in an old digital camera
• Color fringes or jaggies
sensor color sampling pattern
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Where you can see color fringe reconstruction artifacts from your own eye
http://static.flickr.com/21/31393422_23013da003.jpg
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Brewster’s colors—evidence of interpolation from spatially offset color samples
Scale relative to human photoreceptor size: each line covers about 7 photoreceptors.
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Lecture outline
• Color physics. • Color perception
– part 1: assume perceived color only depends on light spectrum.
– part 2: the more general case.
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The assumption for color perception, part 1
• We know color appearance really depends on: – The illumination – Your eye’s adaptation level – The colors and scene interpretation surrounding the
observed color.
• But for now we will assume that the spectrum of the light arriving at your eye completely determines the perceived color.
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How we sense light spectra
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test light, tproject
Cone sensitivities, in matrix, C
L, M, S responses
biophysics: integrate the response over all wavelengths, weighted by the photosensor’s sensitivity at each wavelength.
mathematically: take dot product of input spectrum with the cone sensitivity basis vectors. Project the high-dimensional test light into a 3-d space. R = C t
*=R C t input spectrum
cone sensitivities
cone responses
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To measure a color1. Choose a set of 3 primary colors (three power spectra). 2. Determine how much of each primary needs to be added
to a probe signal to match the test light.
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Con
e se
nsiti
vitie
s
a1 +a3a2 +
Prim
arie
s, P
weighted sum of
primariesproject
L, M, S responsestest light, tproject
Cone sensitivities, Ceye
Ceye t = Ceye P ( )=
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“Color matching functions” tell us how to control primary lights in order to perceptually match a given spectrum
p1 = 645.2 nm p2 = 525.3 nm p3 = 444.4 nm
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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C P = I3x3
why must this hold? Because the amounts of the 3 primaries needed to match the spectrum of each primary (the columns of P) must be [1;0;0], [0;1;0], [0;0;1].
(1) the rows of C must be some (non-degenerate) linear combination of the eye photosensor response curves: C = A Ceye , where A is some 3x3 matrix.
Requirements on C, P to form a color matching system:
(2) for projecting onto C to tell you how much of each primary P is needed to make a perceptual match, C, P must satisfy:
That ensures that if two spectra match when projected into the subspace spanned by C, they will match when projected into the subspace of the eye response curves.
If those conditions hold, then the spectrum PCt will be a perceptual match to t, because Ct = CPCt
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Comparison of color matching functions with best linear combination of cone response curves
Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995
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Displaying Contrast Sensitivity Function (CSF)
along one axis
along other axis
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Contrast Sensitivity Function (CSF)
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Contrast Sensitivity Function (CSF)
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Contrast Sensitivity Function (CSF)
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Another psychophysical fact: luminance and chrominance
channels in the brain
From W. E. Glenn, in Digital Images and Human Vision, MIT Press, edited by Watson, 1993
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luminance, chrominance color components: Y, I, Q
YIQ
⎛
⎝
⎜⎜⎜
⎞
⎠
⎟⎟⎟=
0.299 0.587 0.1140.596 −0.274 −0.3220.211 −0.523 0.312
⎛
⎝
⎜⎜
⎞
⎠
⎟⎟
RGB
⎛
⎝
⎜⎜
⎞
⎠
⎟⎟
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YIQ - RGB
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Spatial resolution and color
R
G
Boriginal
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Blurring the R component
original processed
R
G
B
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Blurring the G component
R
G
B
original processed
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Blurring the B component
original
R
G
Bprocessed
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Lab color components
L
a
b
A rotation of the color coordinates into directions that are more perceptually meaningful: L: luminance, a: red-green, b: blue-yellow
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Blurring the L Lab component
L
a
boriginal processed
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original
Blurring the a Lab component
L
a
bprocessed
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Blurring the b Lab component
original
L
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Lecture outline
• Color physics. • Color perception
– part 1: assume perceived color only depends on light spectrum.
– part 2: the more general case.
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Color constancy demo
• We assumed that the spectrum impinging on your eye determines the object color. That’s often true, but not always. Here’s a counter-example…
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Selected Bibliography
Vision and Art : The Biology of Seeing by Margaret Livingstone, David H. Hubel Harry N Abrams; ISBN: 0810904063 208 pages (May 2002)
Vision Scienceby Stephen E. Palmer MIT Press; ISBN: 0262161834 760 pages (May 7, 1999)
Billmeyer and Saltzman's Principles of Color Technology, 3rd Edition by Roy S. Berns, Fred W. Billmeyer, Max Saltzman Wiley-Interscience; ISBN: 047119459X 304 pages 3 edition (March 31, 2000)
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Selected BibliographyThe Reproduction of Color by R. W. G. Hunt Fountain Press, 1995
Color Appearance Models by Mark Fairchild Addison Wesley, 1998
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Other color references
• Reading: – Chapter 6, Forsyth & Ponce – Chapter 4 of Wandell, Foundations of Vision,
Sinauer, 1995 has a good treatment of this.