Abstract

Previous studies proposed a smart lighting system that can detect object colors and emit spectrally optimized lighting to reduce the light absorbed by surfaces. The spatial resolution of an absorption-minimization light projection system is investigated using images of various visual complexity. Participants with normal color vision and good visual acuity judged the visual clarity of low, medium, and high complexity images by using a mean opinion score (MOS) scale. Results from the visual assessments show that blur acceptability of illuminated images significantly reduces when the circle of confusion (CoC) is increased by 3%. Blur perception also changes with visual complexity.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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  1. D. Durmus and W. Davis, “Optimising light source spectrum for object reflectance,” Opt. Express 23(11), A456–A464 (2015).
    [Crossref] [PubMed]
  2. D. Durmus and W. Davis, “Absorption-Minimizing Spectral Power Distributions,” In Optical Nanostructures and Advanced Materials for Photovoltaics (pp. JTu5A–2). Optical Society of America (2015).
  3. W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
    [Crossref]
  4. D. Durmus and W. Davis, “Appearance of achromatic colors under optimized light source spectrum,” IEEE Photonics J. 10(6), 1–11 (2018).
    [Crossref]
  5. D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
    [Crossref]
  6. D. Durmus and W. Davis, “Object color naturalness and attractiveness with spectrally optimized illumination,” Opt. Express 25(11), 12839–12850 (2017).
    [Crossref] [PubMed]
  7. areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
    [Crossref]
  8. A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).
  9. S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.
  10. ITU-T, “P.910 Subjective video quality assessment methods for multimedia applications,” (2008).
  11. C. C. Carbon, “Art perception in the museum: How we spend time and space in art exhibitions,” i-Perception, 8(1), 11 (2017).
  12. B. Wang and K. J. Ciuffreda, “Depth-of-focus of the human eye: theory and clinical implications,” Surv. Ophthalmol. 51(1), 75–85 (2006).
    [Crossref] [PubMed]
  13. ITU-R, “BT.500-13, Methodology for the subjective assessment of the quality of television pictures,” (2012).
  14. K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
    [Crossref] [PubMed]
  15. F. Crete, T. Dolmiere, P. Ladret, and M. Nicolas, “The blur effect: perception and estimation with a new no-reference perceptual blur metric,” In Human vision and electronic imaging XII (Vol. 6492, p. 64920I). International Society for Optics and Photonics (2007).
  16. A. Rosenberg and B. Ramabhadran, “Bias and Statistical Significance in Evaluating Speech Synthesis with Mean Opinion Scores,” in Interspeech, pp. 3976–3980 (2017).
  17. N. Nachar, “The Mann-Whitney U: A test for assessing whether two independent samples come from the same distribution,” Tutor. Quant. Methods Psychol. 4(1), 13–20 (2008).
    [Crossref]

2018 (2)

D. Durmus and W. Davis, “Appearance of achromatic colors under optimized light source spectrum,” IEEE Photonics J. 10(6), 1–11 (2018).
[Crossref]

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

2017 (2)

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

D. Durmus and W. Davis, “Object color naturalness and attractiveness with spectrally optimized illumination,” Opt. Express 25(11), 12839–12850 (2017).
[Crossref] [PubMed]

2016 (1)

A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).

2015 (1)

2013 (1)

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

2010 (1)

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

2008 (1)

N. Nachar, “The Mann-Whitney U: A test for assessing whether two independent samples come from the same distribution,” Tutor. Quant. Methods Psychol. 4(1), 13–20 (2008).
[Crossref]

2006 (1)

B. Wang and K. J. Ciuffreda, “Depth-of-focus of the human eye: theory and clinical implications,” Surv. Ophthalmol. 51(1), 75–85 (2006).
[Crossref] [PubMed]

Abdalla, D.

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

Álvarez-Fernández, A. B.

A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).

Benítez, A. J.

A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).

Canabal, H.

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Carbon, C. C.

C. C. Carbon, “Art perception in the museum: How we spend time and space in art exhibitions,” i-Perception, 8(1), 11 (2017).

Ciuffreda, K. J.

B. Wang and K. J. Ciuffreda, “Depth-of-focus of the human eye: theory and clinical implications,” Surv. Ophthalmol. 51(1), 75–85 (2006).
[Crossref] [PubMed]

Cufflin, M. P.

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Davis, W.

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

D. Durmus and W. Davis, “Appearance of achromatic colors under optimized light source spectrum,” IEEE Photonics J. 10(6), 1–11 (2018).
[Crossref]

D. Durmus and W. Davis, “Object color naturalness and attractiveness with spectrally optimized illumination,” Opt. Express 25(11), 12839–12850 (2017).
[Crossref] [PubMed]

D. Durmus and W. Davis, “Optimising light source spectrum for object reflectance,” Opt. Express 23(11), A456–A464 (2015).
[Crossref] [PubMed]

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Dawson, K.

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Duis, A.

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

Durmus, D.

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

D. Durmus and W. Davis, “Appearance of achromatic colors under optimized light source spectrum,” IEEE Photonics J. 10(6), 1–11 (2018).
[Crossref]

D. Durmus and W. Davis, “Object color naturalness and attractiveness with spectrally optimized illumination,” Opt. Express 25(11), 12839–12850 (2017).
[Crossref] [PubMed]

D. Durmus and W. Davis, “Optimising light source spectrum for object reflectance,” Opt. Express 23(11), A456–A464 (2015).
[Crossref] [PubMed]

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Fernandez-Balbuena, A. A.

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Hu, R.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Jin, X.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Khan, K. A.

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Luo, X.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Mallen, E. A.

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Mankowska, A.

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Mayorga, S.

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Moliní, D. V.

A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).

Muro, C.

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Nachar, N.

N. Nachar, “The Mann-Whitney U: A test for assessing whether two independent samples come from the same distribution,” Tutor. Quant. Methods Psychol. 4(1), 13–20 (2008).
[Crossref]

Ohno, Y.

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

Vazquez, D.

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

Wang, B.

B. Wang and K. J. Ciuffreda, “Depth-of-focus of the human eye: theory and clinical implications,” Surv. Ophthalmol. 51(1), 75–85 (2006).
[Crossref] [PubMed]

Wang, H.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Xie, B.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Yu, X.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Yu, Z.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Zhang, J.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

Zhang, L.

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

IEEE Photonics J. (2)

areJ. Zhang, R. Hu, B. Xie, X. Yu, X. Luo, Z. Yu, L. Zhang, H. Wang, and X. Jin, “Energy-Saving Light Source Spectrum Optimization by Considering Object’s Reflectance,” IEEE Photonics J. 9(2), 1–11 (2017).
[Crossref]

D. Durmus and W. Davis, “Appearance of achromatic colors under optimized light source spectrum,” IEEE Photonics J. 10(6), 1–11 (2018).
[Crossref]

Leukos (1)

D. Durmus, D. Abdalla, A. Duis, and W. Davis, “Spectral optimization to minimize light absorbed by artwork,” Leukos 10, 1–10 (2018).
[Crossref]

Opción (1)

A. J. Benítez, D. V. Moliní, and A. B. Álvarez-Fernández, “Lighting artworks improving conservation. The Zeus project,” Opción 32(7), 196–214 (2016).

Ophthalmic Physiol. Opt. (1)

K. A. Khan, K. Dawson, A. Mankowska, M. P. Cufflin, and E. A. Mallen, “The time course of blur adaptation in emmetropes and myopes,” Ophthalmic Physiol. Opt. 33(3), 305–310 (2013).
[Crossref] [PubMed]

Opt. Eng. (1)

W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng. 49(3), 033602 (2010).
[Crossref]

Opt. Express (2)

Surv. Ophthalmol. (1)

B. Wang and K. J. Ciuffreda, “Depth-of-focus of the human eye: theory and clinical implications,” Surv. Ophthalmol. 51(1), 75–85 (2006).
[Crossref] [PubMed]

Tutor. Quant. Methods Psychol. (1)

N. Nachar, “The Mann-Whitney U: A test for assessing whether two independent samples come from the same distribution,” Tutor. Quant. Methods Psychol. 4(1), 13–20 (2008).
[Crossref]

Other (7)

D. Durmus and W. Davis, “Absorption-Minimizing Spectral Power Distributions,” In Optical Nanostructures and Advanced Materials for Photovoltaics (pp. JTu5A–2). Optical Society of America (2015).

ITU-R, “BT.500-13, Methodology for the subjective assessment of the quality of television pictures,” (2012).

F. Crete, T. Dolmiere, P. Ladret, and M. Nicolas, “The blur effect: perception and estimation with a new no-reference perceptual blur metric,” In Human vision and electronic imaging XII (Vol. 6492, p. 64920I). International Society for Optics and Photonics (2007).

A. Rosenberg and B. Ramabhadran, “Bias and Statistical Significance in Evaluating Speech Synthesis with Mean Opinion Scores,” in Interspeech, pp. 3976–3980 (2017).

S. Mayorga, D. Vazquez, A. A. Fernandez-Balbuena, H. Canabal, C. Muro, D. Durmus, and W. Davis, “Absorption-minimizing point-by-point light projection system for visual restoration of artwork,” Opt. Express. submitted.

ITU-T, “P.910 Subjective video quality assessment methods for multimedia applications,” (2008).

C. C. Carbon, “Art perception in the museum: How we spend time and space in art exhibitions,” i-Perception, 8(1), 11 (2017).

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Figures (2)

Fig. 1
Fig. 1 The distance between the projector and the painting was 2.4 m, while observers made judgments 1.75 m away from the painting.
Fig. 2
Fig. 2 Luminance of each test image was measured using a handheld luminance meter. Low, medium and high complexity images were represented by Piet Mondrian’s Composition A (a), Grant Wood’s American Gothic (b), and Pieter Bruegel the Elder’s Netherlandish Proverbs (c), respectively.

Tables (8)

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Table 1 Participants judged the visual clarity of projected images using a mean opinion score (MOS) scale.

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Table 2 Visual clarity differences between conditions for the low-complexity image (Composition A) were analyzed using significance testing (95% confidence, p < 0.05* and 99.9% confidence, p < 0.001***).

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Table 3 Visual clarity differences between conditions for the medium-complexity image (American Gothic) were analyzed using significance testing (99.9% confidence, p < 0.001***).

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Table 4 Visual clarity differences between conditions for the high-complexity image (Netherlandish Proverbs) were analyzed using significance testing (95% confidence, p < 0.05* and 99.9% confidence, p < 0.001***).

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Table 5 No statistically significant differences were found in blur perception across image complexity types for the reference condition.

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Table 6 No statistically significant differences were found in blur perception across image complexity types for the low blur condition C1.

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Table 7 Differences in blur perception across image complexity types for the medium-blur condition C2 were analyzed using significance testing (95% confidence, p < 0.05* and 99% confidence, p < 0.01***).

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Table 8 Differences in blur perception across image complexity types for the worst-blur condition C4 were analyzed using significance testing (95% confidence, p < 0.05* and 99% confidence, p < 0.01***).

Equations (4)

Equations on this page are rendered with MathJax. Learn more.

U x = n x n y +(( n x ( n x +1))/2) R x
U y = n x n y +(( n y ( n y +1))/2) R y
σ U = (( n x n y (N+1))/12
Z=(U( n x n y /2))/ σ U

Metrics