How to assess what kind of feeling the lighting scene causes? A new level of computer graphics visualization makes it possible to think about real image through synthetic images from one hand, and from other hand, today the HDRi method allows fixing luminance with an accuracy of up to 10 % in a wide range. Therefore, assessing the lighting quality of designed and existing lighting installations in terms of luminance reaches a new level. It brings the creating of psychophysical model of lighting quality assessment through photometric quantities closer. The structure of the model can be represented in two parts: the calculation equation and the psychophysical scale. This work considers the issue of choosing categories of the psychophysical scale, the method of creating of luminance maps for scene with an arbitrary spatial angle luminance distribution, and the method for evaluating scenes using a new gradient criterion Q based on these maps. An analysis of HDRi images of workplaces based on the experimental setup and scenes in a cafe showed that the Q criterion depends on the type of scene and on the number of light sources in the field of view. One could suggest that it is impossible to create one single psychophysical scale for the Q criterion. However, one can use this new criterion to evaluate the same scenes with different lighting options or similar scenes in terms of spatial luminance distribution and glare. Despite of the luminance map values have an error of about 30 % the using HDRi image of scene allows to calculate Q criterion with an accuracy of about 10 %.
1. Luckiesh, M., Guth, S.K. Luminance in the visual field at borderline between comfort and discomfort // Illuminating Engineering, 1949, Vol. 44, # 11, pp. 650–670.
2. Pierson, C., Wienold, J., Bodart, M. Review of Factors Influencing Discomfort Glare Perception from Daylight // LEUKOS, 2018, # 22:2, pp. 111–148.
3. Pierson, C., Cauwerts, C., Bodart, M., Wienold, J. Tutorial: Luminance Maps for Daylighting Studies from High Dynamic Range Photography // LEUKOS, 2020, Vol. 17, pp. 1–30.
4. Inanici, M. Evaluation of high dynamic range photography as a luminance data acquisition system // Lighting Research & Technology, 2006, # 38, pp. 123–136.
5. Boyce, P.R. Human Factors in Lighting 3rd Edition, CRC Press, 2014.
6. Commission Internationale de l’Eclairage. CIE e-ILV term 17–333 discomfort glare. Vienna (Austria): CIE; [accessed 2019 Oct 16]. http://eilv.cie.co.at/term/333
7. Osterhaus, W.K.E. Discomfort glare assessment and prevention for daylight applications in office environments // Sol Energy, 2005, # 79, pp. 140–158.
8. Aizenberg, Yu.B., Boos, G.V. Reference book on light and engineering, 4th ed. / Editorial office of Light and Engineering, 2019, 892 p.
9. Code of Rules 52.13330.2016 Daylighting and electric lighting. Updated version of SNiP 23–05–95* with revision 1, 2.
10. Kajiya, J.T. The rendering equation // ACM SIGGRAPH Computer Graphics, 1986, Vol. 20, pp 143–150.
11. Jensen, H.W. Global illumination using photon maps // Euro graphics workshop on Rendering techniques, 1996, pp. 21–30.
12. Cuttle, K. Opinion: Lighting criteria for the future // Lighting Research and Technology, 2010, Vol. 42, #3, pp. 270–270.
13. Neumann, D. (Ed.) The Structure of Light: Richard Kelly and the Illumination of Modern Architecture, New Haven, CT: Yale University Press, 2011, 224 p.
14. Bargary, G., Furlan, M., Raynham, P.J., Barbur, J.L., Smith, A.T. Cortical hyperexcitability and sensitivity to discomfort glare // Neuropsychologia, 21, # 10.1016/j.neuropsychologia.2015.02.006.
15. Ashdown, I. Luminance Gradients: Photometric Analysis and Perceptual Reproduction // Journal of the Illuminating Engineering Society, Winter 1996.
16. Budak, V.P., Zheltov, V.S., Meshkova, T.V., Notfullin, R. Sh. Evaluation of illumination quality based on spatial-angular luminance distribution // Light & Engineering, Vol. 25, # 4, 2017, pp. 24–31.
17. Budak, V.P., Zheltov, V.S., Meshkova, T.V., Chembaev, V.D. A new criterion for lighting quality and its approbation in laboratory conditions // Vestnik of the MPEI, 2020, # 1, pp. 73–81.
18. Lombardo, M., Lombardo, G., Lomoriello, D.S., Ducoli, P., Stirpe, M., Serrao, S. Interocular symmetry of parafoveal photoreceptor cone density distribution // Retina, The Journal of retinal and vitreous diseases, 2013, Vol. 33, # 8, pp. 1640–1648.
19. Budak, V.P., Zheltov, V.S., Chembaev, V.D., Meshkova, T.V. Assessment of the quality of indoor lighting in scenes with uneven close sources // GraphiCon Proceedings of the conference, 2018, pp. 411–414.
20. Porsch, T., Funke, C., Schmidt, F., Schierz, Ch. Measurement of the Unified Glare Rating (UGR) based on using ILMD // CIE2015.
21. Zheltov, V.S. Theoretical foundations of modelling the spatial-angular distribution of brightness in lighting installations: abstract of D.T.N.: 05.09.07 / NRU MPEI. M., 2021, 40 p. (abstract of the dissertation).
22. Budak, V.P., Ilyina, E.I. Construction of a psychophysical scale of visual comfort of lighting based on a neural network: preparation of an experiment // Light and Engineering, 2021, # 2, pp. 30–36.
23. Luckiesh, M., Holladay, L.L. Glare and Visibility // Transactions of the IES, 1925, # 20, p. 221.
24. Meshkova, T.V. The quality of lighting with nonuniform distribution of luminance in the field of view abstract. Ph. D.: 05.09.07 / NRU MPEI. M., 2019, 20 p. (abstract of the dissertation).
25. Epaneshnikov, M. M., Ji, X.-Y. Uncomfortable luminance of a single glare source // Light and Engineering, 1963, # 4, pp. 1–6.
26. Pierson, C., Cauwerts, C., Bodart, M., Wienold, J. Tutorial: Luminance Maps for Daylighting Studies from High Dynamic Range Photography // LEUKOS, 2020.

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• HDRi method
• lighting quality criterion
• UGR
• perception scale