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Why is this hard to read

Why is this hard to read

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Why is this hard to read

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  1. Why is this hard to read

  2. Unrelated vs. Related Color • Unrelated color: color perceived to belong to an area in isolation (CIE 17.4) • Related color: color perceived to belong to an area seen in relation to other colors (CIE 17.4)

  3. Illusory contour • Shape, as well as color, depends on surround • Most neural processing is about differences

  4. Illusory contour

  5. CS 768 Color Science • Perceiving color • Describing color • Modeling color • Measuring color • Reproducing color

  6. Spectral measurement • Measurement p(l) of the power (or energy, which is power x time ) of a light source as a function of wavelength l • Usually relative to p(560nm) • Visible light 380-780 nm

  7. Retinal line spread function relative intensity retinal position

  8. monitor intensity retinal intensity Linearity • additivity of response (superposition) • r(m1+m2)=r(m1)+r(m2) • scaling (homogeneity) • r(am)=ar(m) • r(m1(x,y)+m2 (x,y))= r(m1)(x,y)+r(m2)(x,y)= (r(m1)+r(m2))(x,y) • r(am(x,y))=ar(m)(x,y)

  9. Non-linearity

  10. http://webvision.med.utah.edu/

  11. Optic nerve Light Ganglion Amacrine Bipolar Horizontal Cone Rod Epithelium Retinal cross section

  12. Visual pathways • Three major stages • Retina • LGN • Visual cortex • Visual cortex is further subdivided http://webvision.med.utah.edu/Color.html

  13. Optic nerve • 130 million photoreceptors feed 1 million ganglion cells whose output is the optic nerve. • Optic nerve feeds the Lateral Geniculate Nucleus approximately 1-1 • LGN feeds area V1 of visual cortex in complex ways.

  14. Photoreceptors • Cones - • respond in high (photopic) light • differing wavelength responses (3 types) • single cones feed retinal ganglion cells so give high spatial resolution but low sensitivity • highest sampling rate at fovea

  15. Photoreceptors • Rods • respond in low (scotopic) light • none in fovea • try to foveate a dim star—it will disappear • one type of spectral response • several hundred feed each ganglion cell so give high sensitivity but low spatial resolution

  16. Luminance • Light intensity per unit area at the eye • Measured in candelas/m2 (in cd/m2) • Typical ambient luminance levels (in cd/m2): • starlight 10-3 • moonlight 10-1 • indoor lighting 102 • sunlight 105 • max intensity of common CRT monitors 10^2 From Wandell, Useful Numbers in Vision Science http://white.stanford.edu/~brian/numbers/numbers.html

  17. Rods and cones • Rods saturate at 100 cd/m2 so only cones work at high (photopic) light levels • All rods have the same spectral sensitivity • Low light condition is called scotopic • Three cone types differ in spectral sensitivity and somewhat in spatial distribution.

  18. Cones • L (long wave), M (medium), S (short) • describes sensitivity curves. • “Red”, “Green”, “Blue” is a misnomer. See spectral sensitivity.

  19. - - - - + - - - - - - - + + + - + + - + - + + Receptive fields • Each neuron in the visual pathway sees a specific part of visual space, called its receptive field • Retinal and LGN rf’s are circular, with opponency; Cortical are oriented and sometimes shape specific. On center rf Red-Green LGN rf Oriented Cortical rf

  20. Channels Magno Color-blind Fast time response High contrast sensitivity Low spatial resolution Parvo Color selective Slow time response Low contrast sensitivity High spatial resolution Video coding implications Magno Separate color from b&w Need fast contrast changes (60Hz) Keep fine shading in big areas (Definition) Parvo Separate color from b&w Slow color changes OK (40 hz) Omit fine shading in small areas (Definition) (Not obvious yet) pattern detail can be all in b&w channel Channels: Visual Pathways subdivided

  21. Trichromacy • Helmholtz thought three separate images went forward, R, G, B. • Wrong because retinal processing combines them in opponent channels. • Hering proposed opponent models, close to right.

  22. Opponent Models • Three channels leave the retina: • Red-Green (L-M+S = L-(M-S)) • Yellow-Blue(L+M-S) • Achromatic (L+M+S) • Note that chromatic channels can have negative response (inhibition). This is difficult to model with light.

  23. + - +

  24. 100 Luminance 10 1.0 Contrast Sensitivity Red-Green 0.1 Blue-Yellow 0.001 -1 0 1 2 Log Spatial Frequency (cpd)

  25. Color matching • Grassman laws of linearity: (r1 + r2)(l) = r1(l) + r2(l) (kr)(l) = k(r(l)) • Hence for any stimulus s(l) and response r(l), total response is integral of s(l) r(l), taken over all l or approximatelyS s(l)r(l)

  26. Surround light Primary lights Surround field Bipartite white screen Subject Test light Primary lights Test light

  27. Color Matching • Spectra of primary lights s1(l), s2(l), s3(l) • Subject’s task: find c1, c2, c3, such that c1s1(l)+c2s2(l)+c3s3(l)matches test light. • Problems (depending on si(l)) • [c1,c2,c3] is not unique (“metamer”) • may require some ci<0 (“negative power”)

  28. Color Matching • Suppose three monochromatic primaries r,g,b at 645.16, 526.32, 444.44 nm and a 10° field (Styles and Burch 1959). • For any monochromatic light t(l) at l, find scalars R=R(l), G=G(l), B=B(l) such that t(l) = R(l)r + G(l)g + B(l)b • R(l),G(l),B(l) are the color matching functions based on r,g,b.

  29. Color matching • Grassman laws of linearity: (r1 + r2)(l) = r1(l) + r2(l) (kr)(l) = k(r(l)) • Hence for any stimulus s(l) and response r(l), total response is integral of s(l) r(l), taken over all l or approximatelyS s(l)r(l)

  30. Color matching • What about three monochromatic lights? • M(l) = R*R(l) + G*G(l) + B*B(l) • Metamers possible • good: RGB functions are like cone response • bad: Can’t match all visible lights with any triple of monochromatic lights. Need to add some of primaries to the matched light

  31. Surround light Primary lights Surround field Bipartite white screen Subject Test light Primary lights Test light

  32. Color matching • Solution: CIE XYZ basis functions

  33. Color matching • Note Y is V(l) • None of these are lights • Euclidean distance in RGB and in XYZ is not perceptually useful. • Nothing about color appearance

  34. XYZ problems • No correlation to perceptual chromatic differences • X-Z not related to color names or daylight spectral colors • One solution: chromaticity

  35. Chromaticity Diagrams • x=X/(X+Y+Z)y=Y/(X+Y+Z)z=Z/(X+Y+Z) • Perspective projection on X-Y plane • z=1-(x-y), so really 2-d • Can recover X,Y,Z given x,y and on XYZ, usually Y since it is luminance

  36. Chromaticity Diagrams • No color appearance info since no luminance info. • No accounting for chromatic adaptation. • Widely misused, including for color gamuts.

  37. SWOP ENCAD GA ink Some gamuts