COLOR. Elements of color. Visible spectrum. The Human Visual System. The Fovea. There are three types of cones, S, M and L. r( λ)

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1 COLOR Elements of color Angel, 4th ed. 1, 2.5, 7.13 excerpt from Joakim Lindblad Color = The eye s and the brain s impression of electromagnetic radiation in the visual spectra How is color perceived? Visible spectrum light source s( ) reflecting object r( ) detector rods & cones red-sensitive r() green-sensitive g() blue-sensitive b() The Human Visual System rod The Fovea There are three types of cones, S, M and L Ingela Nyström 1

2 Rods Sense luminance, or brightness, but not color. Are spread across the whole retina, and dominate when the pupil is large, i.e., night vision. Less color is seen at night. The response is not linear, but logarithmic. The appearance of an object s intensity depends on the surroundings; the sensation is relative and not absolute. red-sensitive r() green-sensitive g() blue-sensitive b() Three kinds of cones b=435.8nm r=700nm g=546.1nm CIE standard (Commission Internationale de L Eclairage, 1931) wavelength In order to standardize the description of color, a large number of people were instructed to say what combination of basic colors a certain color sample consisted of in standard lighting. This resulted in the color matching curves, i.e., the transform r(),(),() g b x(),(),() y z Color perception Different spectra can result in identical sensations, called metamers Color perception results from the simultaneous stimulation of 3 cone types (trichromat) Our perception of color is affected by surrounding effects and adaptation standard lightsource x object reflectance s( ) r( ) CIE 1931 standard observer x z y x CIE XYZ values = X=14.27 Y=14.31 Z= nm 700nm 400nm 700nm 400nm 700nm X = s( ) r( ) x( ) d Y = s( ) r( ) y( ) d Z = s( ) r( ) z( ) d Each color is represented by a point (X,Y,Z) in the 3D CIE color space. The point is called the tristimulus value. Projection of the CIE XYZ-space RGB/CMY color space Perceptual equal distances RGB - for additive color mixing, e.g., on a computer screen CMY - for subtractive color mixing, e.g., in printing or painting Ingela Nyström 2

3 Mixing light and mixing pigment RGB Additive Subtractive R G B C M Y (K) Mixing light and mixing pigment green yellow RGB within CIE XYZ-space yellow cyan red green red magenta blue magenta blue cyan R C G = M R+B+G=white [] B 1-[] Y (additive) R+G=Y C+M+Y=black (subtractive) C+M=B etc... (CMYK common in printing, where K is the black pigment) HLS color space Hue Lightness Saturation HLS Hue=dominant wavelength, tone Lightness=intensity, brightness Saturation=purity, dilution by white Important aspects: Intensity decoupled from color Related to how humans perceive color Ingela Nyström 3

4 Segmentation of the H image YIQ color space Y= Lightness I= Inphase = amount red-green Q= Quadrature = amount blue-yellow Optimised for transmission (TV broadcast). Compatible with BW monitors (use only Y component) Human eye is more sensitive to variations in lightness than variations in hue and saturation and more bandwith (bits) is used for Y. Mach bands Gamma correction Most displays have non-linear intensity scales. The most common correction method is called gamma correction (usually implemented with a lookup table) Sometimes in computer graphics this effect is exaggerated to compensate for the adaptation of the eye True-color frame buffer Indexed-color frame buffer Store R,G,B values directly in the frame buffer Each pixel requires at least 3 bytes => 2^24 colors Store index into a color map in the frame buffer Each pixel requires at least 1 byte => 2^8 simultaneous colors Ingela Nyström 4

5 Different blending versions (how to combine color values) Additive blending C=A+B e.g., combining light Subtractive blending C=A-(1-B) e.g., filter effect Average blending C=(A+B)/2 or C=uA+vB e.g., for anti-aliasing Hjärnan är lättlurad grön lila gul blå svart Multiplicative blending C=A*B e.g., combining light and matter It is easy to trick the brain green purple yellow blue black Colour context Ingela Nyström 5

6 Shape context Chromatic adaption Ingela Nyström 6