ECE 638: Principles of Digital Color Imaging Systems Lecture 11: Color Opponency.

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Presentation transcript:

ECE 638: Principles of Digital Color Imaging Systems Lecture 11: Color Opponency

Basic spatiochromatic model structure

Opponent stage Trichromatic theory provides the basis for understanding whether or not two spectral power distributions will appear the same to an observer when viewed under the same conditions. However, the trichromatic theory will tell us nothing about the appearance of a stimulus. In the early 1900’s, Ewald Hering observed some properties of color appearance -Red and green never occur together – there is no such thing as a reddish green, or a greenish red -If I add a small amount of blue to green, it looks bluish- green. If I add more blue to green, it becomes cyan. -In contrast, if I add red to green, the green becomes less saturated. If I add enough red to green, the color appears gray, blue, or yellow -If I add enough red to green, the color appears red, but never reddish green

Red-green color opponency

Blue-yellow color opponency

Red-blue and green-blue combinations

Opponent stage (cont.) Hering postulated that there existed two kinds of neural pathways in the visual system -Red-Green pathway fires fast if there is a lot of red, fires slowly if there is a lot of green -Blue-Yellow pathway fires fast if there is a lot of blue, fires slowly if there is a lot of yellow Hering provided no experimental evidence for his theory; and it was ignored for over 50 years

Hue Cancellation Observer looks at patch & makes two observations (no yet) 1) Reddish or greenish (or neither) 2) Bluish or yellowish (or neither) Stimulus Patch Cancelling Stimulus Monochromatic Source Test Stimulus

Hue Cancellation (cont.) Do two experiments separately 1) a. If subject said reddish, add enough green to cancel reddish appearance b. If subject said greenish, add enough red to cancel greenish appearance 2) Perform similar experiment for blue-yellow

Experimental evidence for opponency Hurvitch and Jameson hue cancellation experiment (1955) Savaetichin electrophysiological evidence from the retinal neurons of a fish (1956) Boynton’s color naming experiment (1965) Wandell’s color decorrelation experiment Left and right plots show data for two different observers. Open triangles show cancellation of red- green appearance. Closed circles show cancellation of blue- yellow appearance.

Color spaces that incorporate opponency YUV (NTSC video standard space) YC r C b (Kodak PhotoCD space) L*a*b* (CIE uniform color space) YCxCz (Linearized CIE L*a*b* space) O 1 O 2 O 3 (Wandell’s optimally decorrelated space) 1.Wandell used cone response curves to compute LMS tristimulus values for the colors in the Macbeth Color Checker. 2.He then found a linear transformation to new color coordinates O 1 O 2 O 3 that are maximally decorrelated. Underline colors indicate approximate opponent components O 1 O 2 O 3 forms the basis for the Zhang- Wandell S- CIELAB color space

CIE L*a*b* and its linearized version YCxCz in terms of CIE XYZ CIE L*a*b* L*= 116 f(Y/Y n ) - 16 a*= 200 [ f(X/X n ) - f(Y/Y n ) ] b*= 500 [ f(Y/Y n ) - f(Z/Z n ) ] 7.787x +16/116 0 x x 1/ x1 f(x) =  white point :(X n, Y n, Z n ) Linearized opponent color space Y y C x C z Y y= 116 (Y/Y n ) C x = 200 [ (X/X n ) - (Y/Y n ) ] C z = 500 [ (Y/Y n ) - (Z/Z n ) ] correlate of luminance R-G opponent color chrominance channel Y-B L* -a* +a* -b* +b*

Wandell’s Experiment Background Wandelll’s PCA of Macbeth Color Checker (LMS) Tristimulus data set: i-th patch from Macbeth color checker T yellow

Wandell’s Experiment (cont.) - Achromatic channel measuring lightness - Green-Red - Blue-Yellow

Spectral sensitivities of the Wandell channels Wandell’s sensitivities Hurvetch-Jameson cancelation curves (similar to negative of Wandell sensitivities

Applications of color opponency Example 1: ( ) Kodak PhotoCD : R-G : B-Y Example 2: YUV (D.E. Pearson) Example 3: CIE L*a*b* Gamma-corrected Primary

Wandell’s space in terms of CIE XYZ* *Wen Wu, “Two Problems in Digital Color Imaging: Colorimetry and Image Fidelity Assessor,” Ph.D. Dissertation, Purdue University, Dec. 2000

Visualization of opponent color representation (13.3,o 2,0.17) (13.3,0.24,o 3 ) (Y,0.24,0.17) (Y,o 2,o 3 )