Retinex Theory

1
Retinex Theory

• Psych221 Final Project
• Mike Jahr
• March 16, 2000

2
Color Constancy

• Color depends on wavelength
• But, objects reflect different wavelengths under
  different lighting conditions.
• Banana in daylight, fluorescent light, no
  light...
• To us, they seem to retain their color.

3
How is this possible?

• There is more to color than wavelength.
• The visual system must somehow discount the
  illuminant

4
A Juicy Burger
5
A Closer Look...
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Whats going on?

• Its not very saturated, but the red burger has
  browns, greens, tans
• How can we see these colors in only red and
  white light?

7
Enter Edwin H. Land

• Land was the founder of Polaroid interested in
  color
• While running Maxwells experiments (3 color
  projectors), he noticed this
• It spawned decades of experiments

8
The Mondrian Apparatus

• Land set up 3 filtered light sources (LMS)
• Can calibrate each oneprecisely control light
• Telescopic photometer

Actually closer to a Van Doesburg...
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Mondrian Experiments

• Measure reflectance from a green patch
• Calibrate lights so that a blue patch reflects
  an identical spectrum
• It still looks blue!

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More Mondrian

• Calibrate lights for even reflectance from the
  green patch
• Cover all other patches looks gray
• Uncover all patches looks green

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Lands Conclusions

• Perceived color depends on reflected spectrum,
  but also on surroundings
• Relative reflectance is more important than
  absolute reflectance

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Discount the Illuminant Retinex

• A framework for computing perceived colors on
  the basis of the relative intensities of three
  wavelengths and their spectral interactions.
• Processed in retina or cortex? Retinex!

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Principles of Retinex

• Process each receptor class independently
• Objective is to calculate illuminant-independent
  lightness values
• Lightness values represent perceived color

14
The Algorithm

• Pick a starting pixel x1, then form a path by
  randomly selecting neighboring pixels
• Update an accumulator at each pixel
• Threshold step if difference is small, use
  previous sensor response

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The Algorithm II

• Keep a counter N(x) for each pixel
• After a number of paths, normalize A(x) by N(x)
  for each pixel
• Result is L(x), the lightness value
• Algorithm has two parameters
• number of paths, length of each path

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What is Lightness?

• Should not depend on viewing conditions
• Should only depend on surface properties
• Results in a triplet that is tough to interpret
• The retinex color space
• Issue what to do with it?

17
My Implementation

• 1 Convert image from RGB to LMS via phosphor
  spectra and cone sensitivities
• 2 Run algorithm to get lightness values
• 3 Do something with lightness values??
• BW implementation

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Retinex Variants

• McCann et al.
• Retinex with reset
• Horn
• Determining lightness from an image
• Marini
• Retinex with Brownian motion

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Illusions under Retinex
Original image
Processed image
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More Illusions
Original image
Retinex image
21
Biological Basis

• Some monkey neurons respond to colors, not
  wavelengths
• Cortical area V4 in prestriate cortex
• Even goldfish can discount the illuminant

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Problems with Retinex

• Too dependent on composition of surfaces in
  image
• Higher-order processes influence color

23
Conclusion

• Retinex is a long-lived theory, has sparked much
  debate and many imitators
• Although not a generally accurate model of human
  vision, it does perform well in some situations

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Appendix

• Source files, sample images, sample output, etc.
  can be found in src/ along with brief
  explanations of each.

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References

• E. H. Land, Recent advances in retinex theory
  and some implications for cortical applications
  Color vision and the natural image, Proc. Nat.
  Acad. Sci. USA 80, 51635169 (1983).
• E. H. Land, Recent advances in retinex theory,
  Vision Res. 26, 722 (1986).
• B. K. P. Horn, Determining lightness from an
  image, Comp. Graphics Image Process. 3, 277299
  (1974).
• D. H. Brainard and B. A. Wandell, Analysis of
  the retinex theory of color vision, J. Opt. Soc.
  Am. 3, 16511661 (1986).
• J. J. McCann, Lessons learned from Mondrians
  applied to real images and color gamuts, IST
  Rep. 14, 6 (1999). http//www.imaging.org/pubs/rep
  orter/articles/14_6_mccann/index.html

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References

• E. H. Adelsen, Lightness perception and
  lightness illusions, in M. Gazzaniga, M.S., Ed.,
  The Cognitive Neurosciences, Cambridge, MA MIT
  Press, pp. 339-351 (1999). http//www-bcs.mit.edu
  /people/adelson/publications/gazzan.dir/gazzan.htm
  
• F.W. Campbell, F.R.S., Dr. Edwin H. Land,
  Biographical Memoirs of Fellows of the Royal
  Society, 40, 195-219 (1994). http//www.rowland.or
  g/land/land.html
• D. Marini and L. Marini, Measuring the colours
  we receive, Science Tribune, October (1997).
  http//www.tribunes.com/tribune/art97/mari.htm