1. 03/04/05© 2005 University of Wisconsin Last Time Tone Reproduction –Histogram method –LCIS and improved filter-based methods

2. 03/04/05© 2005 University of Wisconsin Today Gradient Compression algorithms Perceptually driven tone-reproduction Photographically motivated tone reproduction

3. 03/04/05© 2005 University of Wisconsin Local Operators (Again) Recall, local methods attempt to retain contrast without necessarily maintaining relative brightness across the scene There are several variants –Reinhard et. al. is considered one of the best, so it’s what we will talk about –There exist user preference studies to back this up –The non-global version is implemented in PBRT

4. 03/04/05© 2005 University of Wisconsin Reinhard’s Operator Based on principles developed for photography –No surprise it is considered a good operator by viewers A basic global method –Implemented in PBRT A local method: Dodging and Burning

5. 03/04/05© 2005 University of Wisconsin Photographic Tone Reproduction Choose 3 values in scene to map to darkest, brightest and middle in print The value to map to the middle is the key for the scene

6. 03/04/05© 2005 University of Wisconsin Step One: Set the Key Take log-average luminance: And make this equal to the key in the output –a is the key output brightness –Normally use 0.18, but could do 0.09, 0.045, 0.36 or 0.72 –What kind of mapping is this?

7. 03/04/05© 2005 University of Wisconsin Effect of key value

8. 03/04/05© 2005 University of Wisconsin Step Two: Wash out Bright Spots Define a maximal resolvable brightness, L white Start with this equation: –What is the range of output luminance? Then modify it:

9. 03/04/05© 2005 University of Wisconsin On Low Dynamic Range Input

10. 03/04/05© 2005 University of Wisconsin Maybe some problems on HDR

11. 03/04/05© 2005 University of Wisconsin Dodging and Burning Basic idea: Choose key value, a, locally at each point in the image Problem: The size of the local neighborhood must be carefully chosen to avoid halos Implementation: Use center-surround functions to find right scale –V 1 and V 2 are results of Gaussian filter at pixel x,y of scale s

12. 03/04/05© 2005 University of Wisconsin Center-Surround

13. 03/04/05© 2005 University of Wisconsin Detail Parameter 

14. 03/04/05© 2005 University of Wisconsin Final Details Use the following function: Scale input color by display/world luminance ratio: What is this operator aiming to do? Communicate? Perceptually accurate? Art?

15. 03/04/05© 2005 University of Wisconsin Gradient Compression (Fattal, Lischinski, Werman, SIGGRAPH 2002) Instead of reducing the dynamic range of the data directly, reduce the size of the gradients –Ultimate effect is similar, but it’s easier to make it local Reduce large gradients more than small ones –Get most reduction in dynamic range –Small gradients are probably due to texture, large ones due to shadows, occlusion, different surfaces

16. 03/04/05© 2005 University of Wisconsin Gradient Compression in 2D In 1D, you can reduce the gradients and then simply integrate to extract the new signal In 2D, the gradient field has to be conservative To work around this, seek a final image that has the closest legal gradient field to the desired one –Results in a Poison equation over the image –Set appropriate boundary conditions and solve to get the image

17. 03/04/05© 2005 University of Wisconsin Details Work on luminance channel from CIE XYZ Do multi-resolution gradient attenuation –Generate a Gaussian image pyramid –Use central differences to estimate gradient at each level –Attenuate by multiplying by an attenuation function: –Use linear filtering to push low-res results up to high-res

18. 03/04/05© 2005 University of Wisconsin Dealing with Color Work in RGB space for final image For C in (R,G,B) compute: –s between 0.4 and 0.6 worked well Not really the best thing to do

19. 03/04/05© 2005 University of Wisconsin Results

20. 03/04/05© 2005 University of Wisconsin Local Filtering Methods

21. 03/04/05© 2005 University of Wisconsin Ward’s Method

22. 03/04/05© 2005 University of Wisconsin Psychophysics The study of the perception of physical quantities –Does not try to explain anything, just observes what we observe Vital to many areas of graphics –Tone-reproduction: generating the same per perceptual sense with different dynamic range –Rendering Control: Stopping rendering algorithms when the results are no longer perceptible –Error metrics: Comparing images with a sense of what is visually important Ferwerda, Pattanaik, Shirley and Goldberg, SIGGRAPH 1996, is a good reference –The next several slides were borrowed from the paper

23. 03/04/05© 2005 University of Wisconsin Dynamic Range (Again) Note the names for various ranges of perception –Related to which part of the vision system (rods or cones) is functioning effectively

24. 03/04/05© 2005 University of Wisconsin Spectral Sensitivity Incoming radiance is integrated against these curves to get visual response –To match visual response with a different radiance, have to take these curves into account Note in particular the change in color sensitivity –Rods are NOT color sensitive

25. 03/04/05© 2005 University of Wisconsin Detection Thresholds Experiment: Flash a light against a background. How much brighter does the light have to be in order to be noticed? –Sizes measured in degrees of arc Not so important in graphics –Most events we deal with change illumination well beyond the detection threshold

26. 03/04/05© 2005 University of Wisconsin Contrast Thresholds Experiment: Show people a grating. What contrast must be present (difference in foreground/background luminance) for the grating to be distinguishable? Very important to graphics –Places a limit on the maximum useful display resolution –Places a limit on the amount of detail that should be distinguishable in a tone-reproduction algorithm –Useful in measuring the effect of various aliasing and noise effects We might expect the curve on the next slide to flatten out at high luminance. Why?

27. 03/04/05© 2005 University of Wisconsin Contrast Thresholds (Acuity)

28. 03/04/05© 2005 University of Wisconsin Adaptation Measures the effect of transition from light to dark, and vice versa This is light to dark

29. 03/04/05© 2005 University of Wisconsin Adaptation Dark-to-Light

30. 03/04/05© 2005 University of Wisconsin Perceptual Tone Reproduction Various tone reproduction algorithms can be modified to exploit these effects Deliberately reduce contrast if the light level is low Reduce color saturation at low light levels Model adaptation level of viewer over time by manipulating contrast and color

31. 03/04/05© 2005 University of Wisconsin Adjusting for Acuity and Color

32. 03/04/05© 2005 University of Wisconsin Adjusting for Adaptation Not so easy – you can’t make the monitor appear “painfully bright”

33. 03/04/05© 2005 University of Wisconsin Histograms and Perception Ward’s histogram method can be adapted to place limits on resolvable features –Another bound on the magnitude of histogram bins

34. 03/04/05© 2005 University of Wisconsin Other Effects To get color washout, reduce (x,y) by an amount that depends on the average luminance –Formulas in Ward’s and Ferwerda’s papers Veiling is due to light scattering inside the eye –Responsible for the halos around truly bright objects –Ward’s method can handle this –Glare is something different – an adaptation problem

35. 03/04/05© 2005 University of Wisconsin Histograms and Perception