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Adaptive Color Display via
Perceptually-driven Factored
Spectral Projection
Isaac Kauvar, Samuel J Yang, Liang Shi,
Ian Mc...
v
v
v
v
v
Conventional displays produce a limited set of colors.
Conventional displays produce a limited set of colors.
‘display’s gamut’
‘chromaticity diagram’
Limited gamuts prevent accurate color reproduction.
What about content?
Multi-spectral cameras
MicaSense RedEdge Ximea xiSpec
Computer generated
images
Big Buck Bunny
Flexible gamut.
software hardware+
Flexibility yields performance.
sRGB
visualization
of multispectral
target image
Flexibility yields performance.
∆L ∆a ∆b
CIELAB-76 error from target
sRGB
visualization
of multispectral
target image
Flexibility yields performance.
∆L ∆a ∆b
Standard
fixed gamut
CIELAB-76 error from target
sRGB
visualization
of multispect...
Flexibility yields performance.
∆L ∆a ∆b
Standard
fixed gamut
Legacy
flexible gamut
CIELAB-76 error from target
sRGB
visua...
Flexibility yields performance.
∆L ∆a ∆b
Standard
fixed gamut
Legacy
flexible gamut
Our new
flexible gamut
algorithm
CIELA...
Flexibility yields performance.
∆L ∆a ∆b
Standard
fixed gamut
Legacy
flexible gamut
Our new
flexible gamut
algorithm
CIELA...
Hardware implementation.
Works with human users.
What limits the gamut of conventional projectors?
+ +
=
Multiplexed color primaries.
Limitations of current displays.
Human flicker fusion rate: 60 fps
Max frame speed of standard display: 180-240 fps
Maximu...
Limitations of current displays.
Human flicker fusion rate: 60 fps
Max frame speed of standard display: 180-240 fps
Maximu...
Limitations of current displays.
Human flicker fusion rate: 60 fps
Max frame speed of standard display: 180-240 fps
Maximu...
Related work.
Gamut
mapping
Banterle, et. al. 2011
Related work.
Gamut
selection
Gamut
mapping
Banterle, et. al. 2011 Long and Fairchild, 2011
Related work.
Gamut
selection
Li, et. al. 2015
Multiple
projectors
Gamut
mapping
Banterle, et. al. 2011 Long and Fairchild...
Related work.
Gamut
selection
Joint primary
selection
and gamut
mapping
Ben-chorin and Eliav, 2007Li, et. al. 2015
Multipl...
gamut selection
gamut selectiongamut mapping
But human color
perception
is not linear
in CIEXYZ space!
MacAdams 1942
Ellipses scaled by 10.
CIEXYZcolor space
But human color
perception
is not linear
in CIEXYZ space!
MacAdams 1942
Ellipses scaled by 10.
Jung 2011
CIELAB76 color space
Nonlinear
transform
CIEXYZcolor space
Conversion to CIELAB (nonlinear)
Conversion to CIELAB (nonlinear)
Nonconvex!
Reformulate the problem.
Reformulate the problem.
Standard ADMM update rules.
Loop until convergence:
Standard ADMM update rules.
Loop until convergence:
Solve nonlinear
problem on
per-pixel basis
Standard ADMM update rules.
Loop until convergence:
Solve nonlinear
problem on
per-pixel basis
Solve bi-convex
problem
(st...
Convergence.
Performance.
+ + =
Performance.
+ + =
Resulting gamut
Performance.
+ + =
Resulting gamut
Trade
brightness for
color spread
Performance.
+ + =
Error in LAB coordinates Resulting gamut
Trade
brightness for
color spread
Performance.
+ + =
Error in LAB coordinates Error of legacy method
Optimization significantly reduces LAB error.
Optimization consistently reduces LAB error.
Optimization consistently reduces LAB error.
Optimization consistently reduces LAB error.
Our algorithm
It also has better performance with other metrics.
Design of a flexible gamut projector.
Projector calibration.
Projector calibration.
Empirical results.
Empirical results.
Metamer user study corroborates our results.
Our algorithm
Gordon Wetzstein Samuel J Yang
Ian McDowall
computationalimaging.org
www.stanford.edu/~ikauvar
Liang Shi
Wetzstein group h...
5 primaries
5 primaries
Gauss newton step with CIELAB-76
NMF
References
Y. J. Jung, H. Sohn, S. Lee, Y. M. Ro, and H. W. Park, “Quantitative Measurement of Binocular Color Fusion Limi...
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
Adaptive Spectral Projection
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Adaptive Spectral Projection

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Adaptive Spectral Projection

  1. 1. Adaptive Color Display via Perceptually-driven Factored Spectral Projection Isaac Kauvar, Samuel J Yang, Liang Shi, Ian McDowall, Gordon Wetzstein Stanford University
  2. 2. v
  3. 3. v
  4. 4. v
  5. 5. v
  6. 6. v
  7. 7. Conventional displays produce a limited set of colors.
  8. 8. Conventional displays produce a limited set of colors. ‘display’s gamut’ ‘chromaticity diagram’
  9. 9. Limited gamuts prevent accurate color reproduction.
  10. 10. What about content? Multi-spectral cameras MicaSense RedEdge Ximea xiSpec Computer generated images Big Buck Bunny
  11. 11. Flexible gamut. software hardware+
  12. 12. Flexibility yields performance. sRGB visualization of multispectral target image
  13. 13. Flexibility yields performance. ∆L ∆a ∆b CIELAB-76 error from target sRGB visualization of multispectral target image
  14. 14. Flexibility yields performance. ∆L ∆a ∆b Standard fixed gamut CIELAB-76 error from target sRGB visualization of multispectral target image
  15. 15. Flexibility yields performance. ∆L ∆a ∆b Standard fixed gamut Legacy flexible gamut CIELAB-76 error from target sRGB visualization of multispectral target image
  16. 16. Flexibility yields performance. ∆L ∆a ∆b Standard fixed gamut Legacy flexible gamut Our new flexible gamut algorithm CIELAB-76 error from target sRGB visualization of multispectral target image
  17. 17. Flexibility yields performance. ∆L ∆a ∆b Standard fixed gamut Legacy flexible gamut Our new flexible gamut algorithm CIELAB-76 error from target sRGB visualization of multispectral target image
  18. 18. Hardware implementation.
  19. 19. Works with human users.
  20. 20. What limits the gamut of conventional projectors?
  21. 21. + + = Multiplexed color primaries.
  22. 22. Limitations of current displays. Human flicker fusion rate: 60 fps Max frame speed of standard display: 180-240 fps Maximum number of primaries per image: 3-4 ÷ =
  23. 23. Limitations of current displays. Human flicker fusion rate: 60 fps Max frame speed of standard display: 180-240 fps Maximum number of primaries per image: 3-4 ÷ = Columbia multispectral dataset
  24. 24. Limitations of current displays. Human flicker fusion rate: 60 fps Max frame speed of standard display: 180-240 fps Maximum number of primaries per image: 3-4 ÷ = Columbia multispectral dataset But the primaries are different for each image!
  25. 25. Related work. Gamut mapping Banterle, et. al. 2011
  26. 26. Related work. Gamut selection Gamut mapping Banterle, et. al. 2011 Long and Fairchild, 2011
  27. 27. Related work. Gamut selection Li, et. al. 2015 Multiple projectors Gamut mapping Banterle, et. al. 2011 Long and Fairchild, 2011
  28. 28. Related work. Gamut selection Joint primary selection and gamut mapping Ben-chorin and Eliav, 2007Li, et. al. 2015 Multiple projectors Gamut mapping Banterle, et. al. 2011 Long and Fairchild, 2011
  29. 29. gamut selection
  30. 30. gamut selectiongamut mapping
  31. 31. But human color perception is not linear in CIEXYZ space!
  32. 32. MacAdams 1942 Ellipses scaled by 10. CIEXYZcolor space But human color perception is not linear in CIEXYZ space!
  33. 33. MacAdams 1942 Ellipses scaled by 10. Jung 2011 CIELAB76 color space Nonlinear transform CIEXYZcolor space
  34. 34. Conversion to CIELAB (nonlinear)
  35. 35. Conversion to CIELAB (nonlinear) Nonconvex!
  36. 36. Reformulate the problem.
  37. 37. Reformulate the problem.
  38. 38. Standard ADMM update rules. Loop until convergence:
  39. 39. Standard ADMM update rules. Loop until convergence: Solve nonlinear problem on per-pixel basis
  40. 40. Standard ADMM update rules. Loop until convergence: Solve nonlinear problem on per-pixel basis Solve bi-convex problem (standard NMF)
  41. 41. Convergence.
  42. 42. Performance. + + =
  43. 43. Performance. + + = Resulting gamut
  44. 44. Performance. + + = Resulting gamut Trade brightness for color spread
  45. 45. Performance. + + = Error in LAB coordinates Resulting gamut Trade brightness for color spread
  46. 46. Performance. + + = Error in LAB coordinates Error of legacy method
  47. 47. Optimization significantly reduces LAB error.
  48. 48. Optimization consistently reduces LAB error.
  49. 49. Optimization consistently reduces LAB error.
  50. 50. Optimization consistently reduces LAB error. Our algorithm
  51. 51. It also has better performance with other metrics.
  52. 52. Design of a flexible gamut projector.
  53. 53. Projector calibration.
  54. 54. Projector calibration.
  55. 55. Empirical results.
  56. 56. Empirical results.
  57. 57. Metamer user study corroborates our results. Our algorithm
  58. 58. Gordon Wetzstein Samuel J Yang Ian McDowall computationalimaging.org www.stanford.edu/~ikauvar Liang Shi Wetzstein group homepage: Isaac Kauvar’s homepage:
  59. 59. 5 primaries
  60. 60. 5 primaries
  61. 61. Gauss newton step with CIELAB-76
  62. 62. NMF
  63. 63. References Y. J. Jung, H. Sohn, S. Lee, Y. M. Ro, and H. W. Park, “Quantitative Measurement of Binocular Color Fusion Limit for Non-spectral Colors,” Optics Express, vol. 19, no. 8, pp. 7325-7338, 2011 MOHAN, A., RASKAR, R., AND TUMBLIN, J. 2008. Agile spec- trum imaging: Programmable wavelength modulation for cam- eras and projectors. Computer Graphics Forum 27, 2, 709–717. RICE, J. P., BROWN, S. W., ALLEN, D. W., YOON, H. W., LITORJA, M., AND HWANG, J. C. 2012. Hyperspectral image projector applications. vol. 8254, 82540R–82540R–8. AJITO, T., OBI, T., YAMAGUCHI, M., AND OHYAMA, N. 2000. Expanded color gamut reproduced by six-primary projection display. In Proc. SPIE 3954, 130–137. BEN-CHORIN, M., AND ELIAV, D. 2007. Multi-primary design of spectrally accurate displays. Journal of the SID 15, 9, 667–677. BANTERLE, F., ARTUSI, A., AYDIN, T. O., DIDYK, P., EISEMANN, E., GUTIERREZ, D., MANTIUK, R., AND MYSZKOWSKI, K. 2011. Multidimensional image retargeting. In SIGGRAPH Asia 2011 Courses, 15:1–15:612. MACADAM, D. L. 1942. Visual sensitivities to color differences in daylight. OSA JOSA 32, 5, 247–273. LI, Y., MAJUMDER, A., LU, D., AND GOPI, M. 2015. Content- independent multi-spectral display using superimposed projec- tions. Computer Graphics Forum (Eurographics). CHIAO, C.-C., CRONIN, T. W., AND OSORIO, D. 2000. Color signals in natural scenes: characteristics of reflectance spectra and effects of natural illuminants. OSA JOSA A 17, 2, 218–224. DANNEMILLER, J. L. 1992. Spectral reflectance of natural objects: how many basis functions are necessary? OSA JOSA A 9, 4, 507–515.

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