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Understanding the Basics of Color: Physics, Perception, and Color Models

This overview delves into the fundamentals of color, covering essential topics including the physics of illumination, electromagnetic spectra, and material properties. It explains color perception through physiology and psychology and highlights how humans see different colors. The document also examines color mixing methods (both additive RGB and subtractive CMYK) and explores various color spaces like HSV and YIQ. Additionally, techniques such as halftoning and dithering in color representation for printing are discussed, providing clarity on how color is defined and manipulated in computing and visual media.

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Understanding the Basics of Color: Physics, Perception, and Color Models

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Presentation Transcript

  1. Computer Graphics Color

  2. Basics Of Color • elements of color:

  3. Basics of Color • Physics: • Illumination • Electromagnetic spectra • Reflection • Material properties • Surface geometry and microgeometry • Perception • Physiology and neurophysiology • Perceptual psychology

  4. Electromagnetic Spectrum

  5. How well do we see color? • What color do we see the best? • Yellow-green at 550 nm • What color do we see the worst? • Blue at 440 nm • Flashback: Color tables (color maps) for color storage

  6. Humans and Light • when we view a source of light, our eyes respond to • hue: the color we see (red, green, purple) • dominant frequency • saturation: how far is color from grey • how far is the color from gray (pink is less saturated than red, sky blue is less saturated than royal blue) • brightness: how bright is the color • how bright are the lights illuminating the object?

  7. Hue • hue (or simply, "color") is dominant wavelength • integration of energy for all visible wavelengths is proportional to intensity of color

  8. Saturation or Purity of Light • how washed out or how pure the color of the light appears • contribution of dominant light vs. other frequencies producing white light

  9. Intensity, Brightness • intensity : radiant energy emitted per unit of time, per unit solid angle, and per unit projected area of the source (related to the luminance of the source) • brightness : perceived intensity of light

  10. Combining Colors Additive (RGB) Shining colored lightson a white ball Subtractive (CMYK) Mixing paint colors andilluminating with white light

  11. Colour Matching Experiment Mixing of 3 primaries Target colour overlap Adjust intensities to match the colour

  12. RGB Color Space (Color Cube) • Define colors with (r, g, b) amounts of red, green, and blue

  13. CMY Color Model CMY(short for Cyan, Magenta, Yellow, and key) is a subtractive color model.

  14. The CMY Color Model • Cyan, magenta, and yellow are the complements of red, green, and blue • We can use them as filters to subtract from white • The space is the same as RGB except the origin is white instead of black • This is useful for hardcopy devices like laser printers • If you put cyan ink on the page, no red light is reflected

  15. YIQ Color Space • YIQis the color model used for color TV in America. Y is brightness,I & Qare color • Note: Yis the same as CIE’s Y • Result: Use the Y alone and backwards compatibility with B/W TV! • These days when you convert RGB image to B/W image, the green and blue components are thrown away and red is used to control shades of grey (usually)

  16. Converting Color Spaces • Converting between color models can also be expressed as such a matrix transform: • Note the relative unimportance of blue in computing the Y

  17. HSV Color Space • A more intuitive color space • H = Hue • S = Saturation • V = Value (or brightness) Saturation Value Hue

  18. HSV Color Model H S V Color 0 1.0 1.0 Red 120 1.0 1.0 Green 240 1.0 1.0 Blue * 0.0 1.0 White * 0.0 0.5 Gray * * 0.0 Black 60 1.0 1.0 ? 270 0.5 1.0 ? 270 0.0 0.7 ? Figure 15.16&15.17 from H&B

  19. Intuitive Color Spaces

  20. Halftoning • A technique used in newspaper printing • Only two intensities are possible, blob of ink and no blob of ink • But, the size of the blob can be varied • Also, the dither patterns of small dots can be used

  21. Halftoning

  22. Halftoning – dot size

  23. Spatial versus Intensity Resolution • Halftone Approximation: Dither • n ´ n pixels encode n2 + 1 intensity levels • The distribution of intensities is randomized: dither noise, to avoid repeating visual artifacts

  24. Dithering • Halftoning for color images

  25. No Comment Needed • http://www.dokimos.org/ajff/

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