Color 1 Thursday, October 8, 2009
Send me an email fredo@mit.edu Frédo Durand MIT- EECS Thursday, October 8, 2009
Some ideas Use CHDK to provide new features to Canon compact cameras Use flickr API to do something creative Explore different types of gradient reconstructions Improve time lapse Handle small parallax in panoramas Exploit flash/no-flash pairs Editing with images+depth (e.g. from stereo) Smart color to greyscale Face-aware image processing Sharpening out-of-focus images using other pictures from the sequences Application of morphing/warping Motion without movements and automatic illusions Thursday, October 8, 2009
Color Frédo Durand MIT- EECS Many slides courtesy of Victor Ostromoukhov, Leonard McMillan, Bill Freeman Thursday, October 8, 2009
Does color puzzle you? Thursday, October 8, 2009
Puzzles and mysteries • Aren’t colors spectra? Why do we need only 3 numbers to represent them • Are black, and white, colors? • Are primary colors red green and blue? Or red green yellow and blue? where do cyan and magenta come from? • Why is there a color circle? what’s between red and blue? aren’t they at opposite ends of the spectrum? • Should the camera RGB filters be the same as the projector’s RGB filters? Should they be the same as the human eye’s spectral response? Thursday, October 8, 2009
Answer • It’s all linear algebra Thursday, October 8, 2009
Plan • Spectra • Cones and spectral response • Color blindness and metamers • Color matching • Color spaces 8 Thursday, October 8, 2009
color Thursday, October 8, 2009
Spectrum Light is a wave Visible: between 450 and 700nm Thursday, October 8, 2009
Spectrum Light is characterized by its spectrum: amount of energy at each wavelength This is a full distribution: one value per wavelength (infinite number of values) Thursday, October 8, 2009
Light-matter interaction Where spectra come from: - light source spectrum - object reflectance (aka spectral albedo) get multiplied wavelength by wavelength There are different physical processes that explain this multiplication e.g. absorption, interferences = .* Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995 Thursday, October 8, 2009
Alternative: transmittance Also get multiplied = .* Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995 Thursday, October 8, 2009
Examples of reflectance spectra 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. 14 Slide from Bill Freeman Forsyth, 2002 Thursday, October 8, 2009
Examples of illumination spectra Blue sky Tungsten light bulb • Important consequence: the spectrum leaving an object depends on the illumination Foundations of Vision, by Brian Wandell, Sinauer Assoc., 1995 Thursday, October 8, 2009
Questions? • So far, physical side of colors: spectra – an infinite number of values (one per wavelength) 16 Thursday, October 8, 2009
Plan • Spectra • Cones and spectral response • Color blindness and metamers • Color matching • Color spaces 17 Thursday, October 8, 2009
What is Color? E lectromagnetic Wave Spectral Power Distribution Illuminant D65 Reflectance (nm) Spectrum Spectral Power Distribution 18 Slide from Victor Ostromoukhov Thursday, October 8, 2009
What is Color? Neon Lamp Spectral Power Distribution Illuminant F1 Reflectance Spectrum Spectral Power Distribution Under D65 Spectral Power Distribution Under F1 19 Slide from Victor Ostromoukhov Thursday, October 8, 2009
What is Color? O b s e r v e r S tim u lu s 20 Slide from Victor Ostromoukhov Thursday, October 8, 2009
What is Color? M L Spectral Sensibility S of the Ganglion Horizontal L, M and S Cells Cells Rod Cones Bipolar Cone Cells Light Light Amacrine R od s C on es D is tr ib u tion of Cells C on es a n d R od s Retina Optic Nerve 21 Slide from Victor Ostromoukhov Thursday, October 8, 2009
What is Color? R i g h t L G N L e f t L G N Visual Cortex L G N = L a ter a l G en ic u la te N u c leu s 22 Slide from Victor Ostromoukhov Thursday, October 8, 2009
Cones • We focus on low-level aspects of color – Cones and early processing in the retina • We won’t talk about rods (night vision) M L Spectral Sensibility S of the Ganglion Horizontal L, M and S Cells Cells Rod Cones Bipolar Cone Cells Light Light Amacrine R od s C on es D is tr ib u tion of Cells C on es a n d R od s Retina Optic Nerve Thursday, October 8, 2009
Summary (and time for questions) • Spectrum: infinite number of values – can be multiplied – can be added • Light spectrum multiplied by reflectance spectrum – spectrum depends on illuminant • Human visual system is complicated Thursday, October 8, 2009
Plan • What is color • Cones and spectral response • Color blindness and metamers • Fundamental difficulty with colors 25 Thursday, October 8, 2009
Cone spectral sensitivity • Short, Medium and Long wavelength • Response for a cone = ∫ λ stimulus( λ ) * response( λ ) d λ 26 Thursday, October 8, 2009
Cone response Start from infinite number of Stimulus values (one per wavelength) Cone responses Multiply wavelength by wavelength End up with 3 Integrate values (one 27 per cone type) 1 number 1 number 1 number Thursday, October 8, 2009
For matrix lovers • Spectrum: big long vector size N where N= ∞ • Cone response: 3xN matrix of individual responses observed spectrum cone spectral response S M kind of RGB L Thursday, October 8, 2009
For geometry lovers • Spectrum: point in infinite dimensional space • Human vision: 3D linear subspace • Projection infinite set of bases spectrum cone subspace (3D) Thursday, October 8, 2009
Big picture reflectance Light • It’s all linear! multiply Stimulus Cone responses Multiply wavelength by wavelength Integrate 30 Thursday, October 8, 2009
Big picture reflectance Light • It’s all linear! multiply – multiply – add Stimulus • But – non-orthogonal Cone responses bases – infinite dimension – light must be Multiply wavelength by wavelength positive • Depends on light source Integrate 31 Thursday, October 8, 2009
Questions? reflectance Light multiply Stimulus Cone responses Multiply wavelength by wavelength Integrate 32 Thursday, October 8, 2009
A cone does not “see” colors • Different wavelength, different intensity • Same response 33 Thursday, October 8, 2009
Response comparison • Different wavelength, different intensity • But different response for different cones 34 Thursday, October 8, 2009
von Helmholtz 1859: Trichromatic theory • Colors as relative responses (ratios) Violet Blue Orange Yellow Green Violet Green Blue Red Yellow Receptor Responses Orange Red Short wavelength receptors Medium wavelength receptors 400 500 600 700 Long wavelength receptors Wavelengths (nm) 35 Thursday, October 8, 2009
Color names for cartoon spectra cyan red 400 500 600 700 nm 400 500 600 700 nm magenta green 400 500 600 700 nm 400 500 600 700 nm yellow blue 400 500 600 700 nm 400 500 600 700 nm 36 Slide from Bill Freeman Thursday, October 8, 2009
Thursday, October 8, 2009
Questions? 38 Thursday, October 8, 2009
Plan • Spectra • Cones and spectral response • Color blindness and metamers • Color matching • Color spaces 39 Thursday, October 8, 2009
Color blindness • Classical case: 1 type of cone is missing (e.g. red) • Makes it impossible to distinguish some spectra differentiated Same responses 40 Thursday, October 8, 2009
Color blindness – more general • Dalton • 8% male, 0.6% female • Genetic • Dichromate (2% male) – One type of cone missing – L (protanope), M (deuteranope), S (tritanope) • Anomalous trichromat – Shifted sensitivity 41 Thursday, October 8, 2009
Thursday, October 8, 2009
Color blindness test 43 Thursday, October 8, 2009
Color blindness test • Maze in subtle intensity contrast • Visible only to color blinds • Color contrast overrides intensity otherwise 44 Thursday, October 8, 2009
Questions? • Links: – Vischeck shows you what an image looks like to someone who is colorblind. – http://www.vischeck.com/vischeck/ – Daltonize, changes the red/green variation to brightness and – blue/yellow variations. – http://www.vischeck.com/daltonize/ – http://www.vischeck.com/daltonize/runDaltonize.php Thursday, October 8, 2009
Metamers • We are all color blind! • These two different spectra elicit the same cone responses • Called metamers 46 Thursday, October 8, 2009
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