Modeling Luminance Perception at Absolute Threshold
When human luminance perception operates close to its absolute threshold, i. e., the lowest perceivable absolute values, appearance changes substantially compared to common photopic or scotopic vision. In particular, most observers report perceiving temporally‐varying noise. Two reasons are physiolo...
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| Vydané v: | Computer graphics forum Ročník 34; číslo 4; s. 155 - 164 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Oxford
Blackwell Publishing Ltd
01.07.2015
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | When human luminance perception operates close to its absolute threshold, i. e., the lowest perceivable absolute values, appearance changes substantially compared to common photopic or scotopic vision. In particular, most observers report perceiving temporally‐varying noise. Two reasons are physiologically plausible; quantum noise (due to the low absolute number of photons) and spontaneous photochemical reactions. Previously, static noise with a normal distribution and no account for absolute values was combined with blue hue shift and blur to simulate scotopic appearance on a photopic display for movies and interactive applications (e.g., games). We present a computational model to reproduce the specific distribution and dynamics of “scotopic noise” for specific absolute values. It automatically introduces a perceptually‐calibrated amount of noise for a specific luminance level and supports animated imagery. Our simulation runs in milliseconds at HD resolution using graphics hardware and favorably compares to simpler alternatives in a perceptual experiment. |
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| AbstractList | When human luminance perception operates close to its absolute threshold, i. e., the lowest perceivable absolute values, appearance changes substantially compared to common photopic or scotopic vision. In particular, most observers report perceiving temporally‐varying noise. Two reasons are physiologically plausible; quantum noise (due to the low absolute number of photons) and spontaneous photochemical reactions. Previously, static noise with a normal distribution and no account for absolute values was combined with blue hue shift and blur to simulate scotopic appearance on a photopic display for movies and interactive applications (e.g., games). We present a computational model to reproduce the specific distribution and dynamics of “scotopic noise” for specific absolute values. It automatically introduces a perceptually‐calibrated amount of noise for a specific luminance level and supports animated imagery. Our simulation runs in milliseconds at HD resolution using graphics hardware and favorably compares to simpler alternatives in a perceptual experiment. |
| Author | Seidel, Hans-Peter Myszkowski, Karol Ritschel, Tobias Kellnhofer, Petr Eisemann, Elmar |
| Author_xml | – sequence: 1 givenname: Petr surname: Kellnhofer fullname: Kellnhofer, Petr organization: MPI Informatik – sequence: 2 givenname: Tobias surname: Ritschel fullname: Ritschel, Tobias organization: MPI Informatik – sequence: 3 givenname: Karol surname: Myszkowski fullname: Myszkowski, Karol organization: MPI Informatik – sequence: 4 givenname: Elmar surname: Eisemann fullname: Eisemann, Elmar organization: Delft University of Technology – sequence: 5 givenname: Hans-Peter surname: Seidel fullname: Seidel, Hans-Peter organization: MPI Informatik |
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| Copyright | 2015 The Author(s) Computer Graphics Forum © 2015 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. 2015 The Eurographics Association and John Wiley & Sons Ltd. |
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| References_xml | – reference: Kim M.H., Weyrich T., Kautz J.: Modeling human color perception under extended luminance levels. ACM Trans. Graph. (Proc. SIGGRAPH 2009) 28, 3 (2009), 27:1-9. 2 – reference: Wanat R., Mantiuk R.: Simulating and compensating changes in appearance between day and night vision. ACM Trans. Graph. (Proc. SIGGRAPH) 33, 4 (2014). 2 – reference: Reinhard E., Ward G., Debevec P., Pattanaik S., Heidrich W., Myszkowski K.: High Dynamic Range Imaging. Morgan Kaufmann Publishers, 2nd edition, 2010. 2, 4 – reference: Wald G.: Human vision and the spectrum. Science 101 (1945), 653-58. 2 – reference: Riva C., Petrig B.: Blue field entoptic phenomenon and blood velocity in the retinal capillaries. J. Opt. Soc. Am. 70, 10 (1980), 1234-1238. 2 – reference: Janesick J.R.: Scientific charge-coupled devices, vol. 83. SPIE press, 2001. 3 – reference: Palmer S.E.: Vision science: Photons to phenomenology, vol. 1. MIT press Cambridge, 1999. 2 – reference: Wandell B.A.: Foundations of Vision. Sinauer Associates, 1995. 5, 6 – reference: Thompson W.B., Shirley P., Ferwerda J.A.: A spatial post-processing algorithm for images of night scenes. J. Graph. Tools 7, 1 (2002), 1-12. 2, 3, 4, 6, 7, 10 – reference: Jonas J.B., Schneider U., Naumann G.O.: Count and density of human retinal photoreceptors. Graefe's archive for clinical and experimental ophthalmol. 230, 6 (1992), 505-10. 4, 5 – reference: Kass M., Pesare D.: Coherent noise for non-photorealistic rendering. ACM Trans. Graph. (Proc. SIGGRAPH) 30, 4 (2011), 30. 3, 6 – reference: Livingstone M.: Vision and art: the biology of seeing. Harry N. Abrams, 2002. 3 – reference: Khan S.M., Pattanaik S.N.: Modeling blue shift in moonlit scenes by rod cone interaction. J Vis. 4, 8 (2004). 2 – reference: Umino Y., Solessio E., Barlow R.B.: Speed, spatial, and temporal tuning of rod and cone vision in mouse. J Neur 28, 1 (2008), 189-98. 6 – reference: Deering M.: A photon accurate model of the human eye. ACM Trans. Graph. (Proc. SIGGRAPH) 24, 3 (2005), 649-58. 3, 4 – reference: Field G.D., Sampath A.P., Rieke F.: Retinal processing near absolute threshold: from behavior to mechanism. Annu. Rev. Physiol. 67 (2005), 491-514. 4 – reference: Templin K., Didyk P., Myszkowski K., Seidel H.-P.: Perceptually-motivated stereoscopic film grain. Comp. Graph. Forum (Proc. Pacific Graphics) 33, 7 (2014). 3 – reference: Watson A.B., Yellott J.I.: A unified formula for light-adapted pupil size. J Vis 12 (2012). 4 – reference: Kirk A.G., O'Brien J.F.: Perceptually based tone mapping for low-light conditions. ACM Trans. Graph. (Proc. SIGGRAPH) 30, 4 (2011), 42:1-10. 2 – reference: Hecht S., Shlaer S., Pirenne M.H.: Energy, quanta, and vision. J Gen Phys 25, 6 (1942), 819-840. 2, 3, 4, 5 – reference: Kellnhofer P., Ritschel T., Vangorp P., Myszkowski K., Seidel H.-P.: Stereo day-for-night: Retargeting disparity for scotopic vision. ACM Trans. Appl. Percept. 11, 3 (2014), 15:1-17. 3 – reference: Lillywhite P.: Multiplicative intrinsic noise and the limits to visual performance. Vis. Res. 21, 2 (1981), 291-296. 4, 5 – reference: Teich M., Prucnal P.R., Vannucci G., Breton M.E., McGilL W.J.: Multiplication noise in the human visual system at threshold. J. Opt. Soc. Am., 72, 4 (1982), 419-31. 4 – reference: Alpern M.: Rhodopsin kinetics in the human eye. J Phys. 217, 2 (1971), 447-471. 2 – reference: Barlow H.B.: Retinal noise and absolute threshold. J. Opt. Soc. Am. 46, 8 (1956), 634-639. 2, 4 – reference: Ritschel T., Eisemann E.: A computational model of afterimages. Comp. Graph. Forum (Proc. EG) 31, 2 (2012), 529-534. 2 – reference: Ashmore F., Falk G.: Dark noise in retinal bipolar cells and stability of rhodopsin in rods. Nature 270 (1977), 69-71. 4 – reference: Baylor D., Lamb T., Yau K.-W.: Responses of retinal rods to single photons. J Phys. 288, 1 (1979), 613-34. 4 – reference: Mariani A.P., Kolb H., Nelson R.: Dopamine-containing amacrine cells of Rhesus monkey retina parallel rods in spatial distribution. Brain Res. 322, 1 (1984), 1-7. 5 – reference: Shlaer S.: The relation between visual acuity and illumination. J Gen Phys 21 (1937), 165-188. 2 – reference: Yau K., Matthews G., Baylor D.: Thermal activation of the visual transduction mechanism in retinal rods. Nature 279 (1979), 806-7. 4 – reference: Kurihara T., Manabe Y., Aoki N., Kobayashi H.: Digital image improvement by adding noise: An example by a professional photographer. In Image Quality and System Performance V (2008), vol. 6808 of SPIE, pp. 1-10. 3 – reference: Bloch A.M.: Experience sur la vision. C.r. Séanc. Soc. Biol. 37 (1885), 493-495. 4 – reference: Smith S.W.: The scientist and engineer's guide to digital signal processing. California Technical Pub., 1997. 6 – year: 2011 – volume: 33 issue: 4 year: 2014 article-title: Simulating and compensating changes in appearance between day and night vision publication-title: ACM Trans. Graph. (Proc. SIGGRAPH) – volume: 270 start-page: 69 year: 1977 end-page: 71 article-title: Dark noise in retinal bipolar cells and stability of rhodopsin in rods publication-title: Nature – volume: 21 start-page: 165 year: 1937 end-page: 188 article-title: The relation between visual acuity and illumination publication-title: J Gen Phys – volume: 230 start-page: 505 issue: 6 year: 1992 end-page: 10 article-title: Count and density of human retinal photoreceptors publication-title: Graefe's archive for clinical and experimental ophthalmol – start-page: 333 year: 2005 end-page: 338 – start-page: 24 year: 2000 end-page: 30 – start-page: 49 year: 2005 end-page: 52 – volume: 33 issue: 7 year: 2014 article-title: Perceptually‐motivated stereoscopic film grain publication-title: Comp. Graph. Forum (Proc. Pacific Graphics) – volume: 288 start-page: 613 issue: 1 year: 1979 end-page: 34 article-title: Responses of retinal rods to single photons publication-title: J Phys – volume: 21 start-page: 291 issue: 2 year: 1981 end-page: 296 article-title: Multiplicative intrinsic noise and the limits to visual performance publication-title: Vis. Res – volume: 279 start-page: 806 year: 1979 end-page: 7 article-title: Thermal activation of the visual transduction mechanism in retinal rods publication-title: Nature – year: 1977 – volume: 30 start-page: 42:1 issue: 4 year: 2011 end-page: 10 article-title: Perceptually based tone mapping for low‐light conditions publication-title: ACM Trans. Graph. (Proc. 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| SubjectTerms | Categories and Subject Descriptors (according to ACM CCS) Computer animation Computer graphics Computer simulation Games Human body I.3.3 [Computer Graphics]: Picture/Image Generation-Viewing algorithms Lighting Luminance Noise Perception Photons Spontaneous Studies Thresholds |
| Title | Modeling Luminance Perception at Absolute Threshold |
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