Colour. Leow Wee Kheng. CS4243 Computer Vision and Pattern Recognition.
CS4243. Colour. 1 ..... Billmeyer and Saltzman's Principles of Color. Technology.
Leow Wee Kheng CS4243 Computer Vision and Pattern Recognition
Colour
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Colour is everywhere!
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You already know enough about colour? Let’s do a test…
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+ CS4243
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+ CS4243
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+ CS4243
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So, there’s a lot more to colour!
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Human Colour Perception
Human’s eye has retina that senses light.
retina
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Human’s retina has 2 kinds of light receptors: Rods:
sensitive to amount of light Cones:
sensitive to lights of different wavelengths
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Cones are sensitive to various colours Wavelengths
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from 400nm (violet) to 700nm (red)
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3 kinds of cones: Short
(S): most sensitive to blue Medium (M): most sensitive to green Long (L): most sensitive to red
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Cones send signals to brain.
Brain interprets mixture of signals as colours.
That’s why colours are coded with 3 values.
Different coding schemes give different colour spaces.
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RGB Colour Space
Colour is coded with 3 values (red, green, blue)
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Each value is an unsigned 8-bit value: (0,
0, 0) is black (255, 0, 0) is red (0, 255, 0) is green (0, 0, 255) is blue (128, 128, 128) is gray (255, 255, 255) is white
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HSV Colour Space
Code colour as hue, saturation, value. Also
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called HSB (B for brightness).
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Hue colour
type 0° (red) to 360°
Saturation Colourfulness 0
to 1 (full colour)
Value Brightness 0
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(black) to 1 (white)
More intuitive than RGB. Colour
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HSL Colour Space
Code colour as hue, saturation, lightness. Similar
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to HSV, also called HLS.
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Hue colour
type 0° (red) to 360°
Saturation Colourfulness 0
to 1 (full colour) Full saturation defined at L = 0.5
Lightness 0
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(black) to 1 (white)
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YCbCr Colour Space
Code colour as Y, Cb, Cr. Used
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for TV, video.
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Y: luminance
Cb: blue difference
Cr: red difference
For unsigned 8-bit encoding, these values range from 0 to 255.
Often confused with YUV.
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Colour Difference
Consider two colours C1 and C2.
How to measure difference between C1 and C2?
Simplest difference measure: Euclidean distance
d (C1 , C2 ) = Straight
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(R1 − R2 ) + (G1 − G2 ) + (B1 − B2 ) 2
2
2
line distance in RGB space.
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Let’s do a test… Which colour looks more similar to the middle colour, left or right?
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Perceptually Uniform Colour Spaces
RGB space is not perceptually uniform colour distance ⇒ equal perceptual difference Inappropriate if need to match human perception. Equal
HSV, HSL, YCbCr also not perceptually uniform.
Perceptually (more) uniform colour spaces: Munsell
colour space
CIELAB CIELUB
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Munsell Colour Space
Code colour as hue, value, chroma. chroma:
colourfulness Difficult to use.
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CIELAB
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CIE 1976 L*a*b* colour space
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L* : matches human perception of lightness From
0 (black) to 100 (white).
a*, b*: hue
+b
yellow
green
red
−a
+a
−b CS4243
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CIELUV
CIE 1976 L*u*v* Similar
to CIELAB colour space. L* : range from 0 to 100. u*, v*: typically range from –100 to +100.
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Colour Arithmetic
How to add, subtract, average colours correctly?
If not careful, can produce invalid colours.
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Addition
With unsigned 8-bit, cannot have value > 255.
Usually clip to maximum value.
For example,
R1 + R2 R= 255
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if R1 + R2 < 255 otherwise
Similarly for G, B.
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image sum 2 1
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image sum 2 1
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Subtraction
With unsigned 8-bit, cannot have value < 0.
Usually clip to minimum value.
For example,
R1 − R2 R= 0
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if R1 − R2 > 0 otherwise
Similarly for G, B.
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difference image 2 1
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difference image 2 1
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Average
Usual way of computing mean: n
sum
S = ∑ Ri i =1
divide With
unsigned 8-bit value, S can overflow for small n.
Clipping Need
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1 M= S n
S produces inaccurate average.
better methods.
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Average
Method 1: Floating point representation. Then, S doesn’t overflow unless n is very large. S is not a valid colour value. 1 S truncated to unsigned 8-bit is valid. Mean M = n
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Average
Method 2: Incremental average With only 1 colour R1, mean = R1 M 1 = R1
With
two colours R1, R2,
1 1 1 M 2 = (R1 + R2 ) = M 1 + R2 2 2 2 With k colours R1, R2,…, Rk, 1 k −1 1 M k = (R1 + + Rk ) = M k −1 + Rk k k k k −1 1 M k −1 , Rk are all valid colours. Mk, k k CS4243
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image mean 2 1
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image mean 2 1
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mean over 8-sec video
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Colour-Difference Equations
Consider a reference colour C0.
Euclidean distance of C1 from C0 in CIELAB / CIELUV space:
More
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perceptually uniform than in RGB space. Colour
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Can also define as:
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Further improvements: CIE94, CMC, BFD.
More perceptually uniform than Euclidean distance in CIELAB / CIELUV colour space.
CIE94
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Summary
Colours have 3 components.
Most colour spaces are not perceptually uniform.
CIELAB/CIELUV are perceptually more uniform.
Be careful with colour arithmetic.
Use appropriate colour-difference equation.
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Further Reading
Conversion formulae for colour spaces OpenCV
user guide Wikipedia
Colour-difference equations: [Leow2002]
CIE94, CMC, BFD: [Berns2000, Leow2002]
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References
R. S. Berns. Billmeyer and Saltzman’s Principles of Color Technology. John Wiley & Sons, 3 edition, 2000.
W. K. Leow, Color Spaces and Color-Difference Equations. Tech Report, NUS, 2002.
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