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Journal articles on the topic 'Brightness perception'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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1

Lv, Fule, Dabo Guo, Shuai Yang, and Guang Yuan. "P‐3.6: Study on the distribution of perceived brightness level based on HK effect in three‐dimensional CIELAB color space of laser display." SID Symposium Digest of Technical Papers 55, S1 (April 2024): 734–37. http://dx.doi.org/10.1002/sdtp.17189.

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The current trend in display technology is towards achieving larger color gamut and higher brightness levels. However, it should be noted that visual perception of brightness intensity may differ from physical brightness intensity. The HelmholtzKohlrausch effect(H‐K effect) refers to the phenomenon where the perceived brightness of a color increases as its purity or saturation increases while keeping its luminance constant. In order to investigate the relationship between visual perception brightness and lightness, hue and color purity, an experiment was conducted using an RGB laser television as the display device. A total of 12 subjects participated in the visual perception brightness experiment. Based on the experimental results, the visual perceptual brightness for different color patterns was determined. Subsequently, a multilayer perceptron neural network was employed to depict the variation pattern of visual perception of brightness within the CIELAB color space. Finally, Fairchild's H‐K effect compensation formula was revised using nonlinear least squares method based on these experimental findings.

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2

Cornelissen, F. W., A. R. Wade, R. F. Dougherty, and B. A. Wandell. "fMRI of brightness perception." Journal of Vision 3, no. 9 (March 18, 2010): 57. http://dx.doi.org/10.1167/3.9.57.

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3

Gove, Alan, Stephen Grossberg, and Ennio Mingolla. "Brightness perception, illusory contours, and corticogeniculate feedback." Visual Neuroscience 12, no. 6 (November 1995): 1027–52. http://dx.doi.org/10.1017/s0952523800006702.

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AbstractA neural network model is developed to explain how visual thalamocortical interactions give rise to boundary percepts such as illusory contours and surface percepts such as filled-in brightnesses. Top-down feedback interactions are needed in addition to bottom-up feed-forward interactions to simulate these data. One feedback loop is modeled between lateral geniculate nucleus (LGN) and cortical area V1, and another within cortical areas V1 and V2. The first feedback loop realizes a matching process which enhances LGN cell activities that are consistent with those of active cortical cells, and suppresses LGN activities that are not. This corticogeniculate feedback, being endstopped and oriented, also enhances LGN ON cell activations at the ends of thin dark lines, thereby leading to enhanced cortical brightness percepts when the lines group into closed illusory contours. The second feedback loop generates boundary representations, including illusory contours, that coherently bind distributed cortical features together. Brightness percepts form within the surface representations through a diffusive filling-in process that is contained by resistive gating signals from the boundary representations. The model is used to simulate illusory contours and surface brightnesses induced by Ehrenstein disks, Kanizsa squares, Glass patterns, and cafe wall patterns in single contrast, reverse contrast, and mixed contrast configurations. These examples illustrate how boundary and surface mechanisms can generate percepts that are highly context-sensitive, including how illusory contours can be amodally recognized without being seen, how model simple cells in V1 respond preferentially to luminance discontinuities using inputs from both LGN ON and OFF cells, how model bipole cells in V2 with two colinear receptive fields can help to complete curved illusory contours, how short-range simple cell groupings and long-range bipole cell groupings can sometimes generate different outcomes, and how model double-opponent, filling-in and boundary segmentation mechanisms in V4 interact to generate surface brightness percepts in which filling-in of enhanced brightness and darkness can occur before the net brightness distribution is computed by double-opponent interactions.

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4

Guan, Shuchen, Matteo Toscani, and Karl Gegenfurtner. "Heterochromatic brightness perception of illuminants." Journal of Vision 22, no. 14 (December 5, 2022): 4022. http://dx.doi.org/10.1167/jov.22.14.4022.

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5

Paradiso, Michael A., and Ken Nakayama. "Brightness perception and filling-in." Vision Research 31, no. 7-8 (January 1991): 1221–36. http://dx.doi.org/10.1016/0042-6989(91)90047-9.

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6

He, Nailong, Yuning Zhang, Xinhang Ling, Chenhao Hu, Chenyu Huang, Lan He, and Baoping Wang. "P‐3.2: A Study on Perceptual Brightness Model Related to Pupil Size." SID Symposium Digest of Technical Papers 55, S1 (April 2024): 716–19. http://dx.doi.org/10.1002/sdtp.17185.

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The mismatch between physical brightness and perceived brightness of display devices in different light environments is increasingly serious. This paper analyzes the perception mechanism of display brightness according to the structure and perception characteristics of human visual system. Different display stimuli were further designed for visual perception experiments, and the influence of relevant objective quantities on the evaluation of perceived brightness was studied, so as to establish a display brightness perception model based on retinal imaging. Ultimately, the perceived brightness of the display can be characterized by the display of physical luminance and pupil diameter, and it has a high correlation with the perceived experimental values.

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7

Huang, Xin, Sean P. MacEvoy, and Michael A. Paradiso. "Perception of Brightness and Brightness Illusions in the Macaque Monkey." Journal of Neuroscience 22, no. 21 (November 1, 2002): 9618–25. http://dx.doi.org/10.1523/jneurosci.22-21-09618.2002.

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8

Rossi, Andrew F., and Michael A. Paradiso. "Temporal limits of brightness induction and mechanisms of brightness perception." Vision Research 36, no. 10 (May 1996): 1391–98. http://dx.doi.org/10.1016/0042-6989(95)00206-5.

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9

He, Nailong, Yuning Zhang, Chenyu Huang, Wei Wang, and Baoping Wang. "P‐3.1: Research on Display Brightness Perception and Visual Comfort Representation Model." SID Symposium Digest of Technical Papers 54, S1 (April 2023): 615–19. http://dx.doi.org/10.1002/sdtp.16367.

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People's perception of brightness and visual comfort in different light environments are important indicators of display products. The perception of the brightness of the human eye is often different from the actual brightness of the display. This is because there is a difference between the perceived brightness and the physical brightness. The luminous body of the same physical brightness may give people different feelings, thus producing different perceived brightness. In the complex optical environment, the existing photoelectric measurement parameters may not be able to accurately describe the perception effect of the display device. The research on perceived brightness and visual comfort has a long history, but in view of the increasingly complex light environment and the development of diversified display equipment, the perceptual brightness model needs to be further modified and improved. Based on the modeling research of perceived brightness, this paper studies the perception mechanism of human eyes, analyzes the shortcomings of the current mainstream or new display devices, and proposes a more comfortable display technology based on people's viewing habits, ambient light and display content.

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10

Russo, Frank A., Dominique T. Vuvan, and William Forde Thompson. "Vowel Content Influences Relative Pitch Perception in Vocal Melodies." Music Perception 37, no. 1 (September 1, 2019): 57–65. http://dx.doi.org/10.1525/mp.2019.37.1.57.

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Note-to-note changes in brightness are able to influence the perception of interval size. Changes that are congruent with pitch tend to expand interval size, whereas changes that are incongruent tend to contract. In the case of singing, brightness of notes can vary as a function of vowel content. In the present study, we investigated whether note-to-note changes in brightness arising from vowel content influence perception of relative pitch. In Experiment 1, three-note sequences were synthesized so that they varied with regard to the brightness of vowels from note to note. As expected, brightness influenced judgments of interval size. Changes in brightness that were congruent with changes in pitch led to an expansion of perceived interval size. A follow-up experiment confirmed that the results of Experiment 1 were not due to pitch distortions. In Experiment 2, the final note of three-note sequences was removed, and participants were asked to make speeded judgments of the pitch contour. An analysis of response times revealed that brightness of vowels influenced contour judgments. Changes in brightness that were congruent with changes in pitch led to faster response times than did incongruent changes. These findings show that the brightness of vowels yields an extra-pitch influence on the perception of relative pitch in song.

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11

Takeuchi, Tetsuji. "The Fundamental Properties of Brightness Perception." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 81, no. 6 (1997): 493–99. http://dx.doi.org/10.2150/jieij1980.81.6_493.

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12

Nayatani, Yoshinobu, Yoshifumi Umemura, Kenjiro Hashimoto, Hiroaki Sobagaki, and Kotaro Takahama. "Brightness perception of chromatic object color." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 72, Appendix (1988): 102–3. http://dx.doi.org/10.2150/jieij1980.72.appendix_102.

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13

Royer, Michael P., and Kevin W. Houser. "Spatial Brightness Perception of Trichromatic Stimuli." LEUKOS 9, no. 2 (October 1, 2012): 89–108. http://dx.doi.org/10.1582/leukos.2012.09.02.002.

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14

Loetterle, Francis E., Richard A. Beck, and Jim Carlson. "Public Perception of Pavement-Marking Brightness." Transportation Research Record: Journal of the Transportation Research Board 1715, no. 1 (January 2000): 51–59. http://dx.doi.org/10.3141/1715-08.

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The Minnesota Department of Transportation (MnDOT) conducted research to establish a threshold value of retroreflectivity for use in its pavement-marking management program. Members of the general public were invited to drive MnDOT automobiles on a driving course of state and county roads. An interviewer rode along with each study participant asking questions about the brightness (or luminance) of pavement markings within predetermined sections of roadway. The interview was conducted after dark with the car’s headlights at low beam. For each section of roadway, study participants were asked to grade the visibility of the pavement markings; the edge line and the centerline were evaluated individually. The average scores received from all study participants for a specific section were compared with retroreflectivity data taken by MnDOT’s mobile retroreflectometer. Analysis of the data revealed an apparent correlation between the readings taken by the retroreflectometer and the rating scores provided by the study participants. This analysis also suggested that the threshold value of acceptable retroreflectivity versus unacceptable retroreflectivity was between 80 and 120 mcd/m2/lx when using the Laserlux® retroreflectometer. In its continuing effort to improve “customer service,” MnDOT has committed to providing durable pavement markings that are visible year-round and is purchasing equipment and training personnel to implement this program. As a result of the market research project, MnDOT will use 120 mcd/m2/lx as the threshold between acceptable retroreflectivity and unacceptable retroreflectivity when developing the new pavement-marking management program. The establishment of a threshold retroreflectivity value also will allow cost-benefit and life-cycle analyses of different pavement-marking materials and help MnDOT to grade itself on how well it is meeting customer expectations.

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15

Martin, Timothy J., and G. D. Robison. "Instrument for Measuring Relative Brightness Perception." American Journal of Ophthalmology 117, no. 5 (May 1994): 625–31. http://dx.doi.org/10.1016/s0002-9394(14)70068-6.

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16

Grossberg, Stephen, and Frank Kelly. "Neural dynamics of binocular brightness perception." Vision Research 39, no. 22 (November 1999): 3796–816. http://dx.doi.org/10.1016/s0042-6989(99)00095-4.

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17

Rönnberg, Niklas. "Sonification supports perception of brightness contrast." Journal on Multimodal User Interfaces 13, no. 4 (July 18, 2019): 373–81. http://dx.doi.org/10.1007/s12193-019-00311-0.

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18

Ling, Xinhang, Yuning Zhang, Nailong He, Chenyu Huang, Chenhao Hu, and Lan He. "P‐3.10: A Model‐based Study on Perceived Brightness under Various Ambient Illuminance Levels." SID Symposium Digest of Technical Papers 55, S1 (April 2024): 749–52. http://dx.doi.org/10.1002/sdtp.17193.

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Through psychophysical experiments, the study investigated the effects of ambient illuminance and screen luminance on perceived brightness and pupil diameter. The results indicate a close correlation between perceived brightness and both screen luminance and ambient illuminance. The changes in pupil diameter reflect to some extent the changes in brightness perception. A preliminary brightness perception model was established to quantitatively predict how the human eye perceives screen luminance.

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19

Shimakura, Hitomi, and Katsuaki Sakata. "Desaturation-Induced Brightness in Face Color Perception." i-Perception 10, no. 3 (May 2019): 204166951985478. http://dx.doi.org/10.1177/2041669519854782.

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The distinctiveness of perception of face from nonface objects has been noted previously. However, face brightness is often confounded with whiteness in the beauty industry; few studies have examined these perceptual differences. To investigate the interactions among face color attributes, we measured the effect of saturation on brightness and whiteness in both uniform color patches and face images to elucidate the relationship between these two perceptions. We found that, at constant luminance, a uniform color patch looked brighter with an increase in saturation (i.e., the Helmholtz–Kohlrausch effect occurred), while in contrast, brightness of a facial skin image looked less bright with increased saturation (i.e., contrary to the Helmholtz–Kohlrausch effect), which suggested this interaction of color attributes was influenced by top-down information. We conclude that this inverse effect of saturation on brightness for face images is not due to face recognition, color range of the skin tone, the luminance distribution, or recognition of human skin but due to the composite interactions of these facial skin factors in higher order recognition mechanisms.

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20

Vincent, Joris, Marianne Maertens, and Guillermo Aguilar. "Perceptual Brightness Scales for White’s Effect Constrain Computational Models of Brightness Perception." Journal of Vision 22, no. 14 (December 5, 2022): 4160. http://dx.doi.org/10.1167/jov.22.14.4160.

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21

Istiqomah, Novera, Yuya Kinzuka, Tetsuto Minami, and Shigeki Nakauchi. "Brightness Perception in World-Centered Coordinates Assessed by Pupillometry." Behavioral Sciences 13, no. 1 (January 9, 2023): 60. http://dx.doi.org/10.3390/bs13010060.

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Subjective brightness perception reportedly differs among the peripheral visual fields owing to lower- and higher-order cognition. However, there is still a lack of information associated with subjective brightness perception in the world-centered coordinates, not in the visual fields. In this study, we aimed to investigate the anisotropy of subjective brightness perception in the world-centered coordinates based on pupillary responses to the stimuli in five locations by manipulating the world-centered coordinates through active (requiring head movement) and passive scenes (without head movement) in a virtual reality environment. Specifically, this study aimed to elucidate if there is an ecological advantage in the five different locations in the world-centered coordinates. The pupillary responses to glare and halo stimuli indicated that the brightness perception differed among the five locations in the world-centered coordinates. Furthermore, we found that the pupillary response to stimuli at the top location might be influenced by ecological factors (such as from the bright sky and the sun’s existence). Thus, we have contributed to the understanding of the extraretinal information influence on subjective brightness perception in the world-centered coordinates, demonstrating that the pupillary response is independent of head movement.

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22

Bowen, Richard W. "Consistency of individual differences in brightness perception." Perception & Psychophysics 40, no. 3 (May 1986): 159–63. http://dx.doi.org/10.3758/bf03203011.

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23

Watanuki, Tasuku, Hiroshi Takahashi, and Takashi Irikura. "Brightness Perception Throughout the Entire Visual Field." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 99, no. 5 (2015): 258–62. http://dx.doi.org/10.2150/jieij.99.258.

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24

Morita, Kazumoto, Jinichi Mashiko, Shinichiro Itoh, and Takeo Okada. "Brightness Perception of Automobile Head-Up Displays." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 80, no. 2 (1996): 104–12. http://dx.doi.org/10.2150/jieij1980.80.2_104.

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25

Sagawa, Ken, and Keishiro Takeichi. "Mesopic photometry system based on brightness perception." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 70, Appendix (1986): 78. http://dx.doi.org/10.2150/jieij1980.70.appendix_78.

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26

Ludwig, Michael, and Gary Meyer. "Brightness Perception of Surfaces with Mesoscale Structures." Journal of Imaging Science and Technology 61, no. 2 (March 1, 2017): 205041–2050413. http://dx.doi.org/10.2352/j.imagingsci.technol.2017.61.2.020504.

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27

Fischer, Stefan. "Modeling brightness perception and syntactical image coding." Optical Engineering 34, no. 7 (July 1, 1995): 1900. http://dx.doi.org/10.1117/12.200602.

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28

Costa, Marcelo. "Edge influences on suprathreshold white brightness perception." Journal of Vision 15, no. 12 (September 1, 2015): 637. http://dx.doi.org/10.1167/15.12.637.

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29

Freyssinier, J. P., M. S. Rea, and J. D. Bullough. "Brightness contrast perception in the mesopic region." Ophthalmic and Physiological Optics 26, no. 3 (May 2006): 300–312. http://dx.doi.org/10.1111/j.1475-1313.2006.00322.x.

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30

Peromaa, Tarja-L., and Pentti I. Laurinen. "Separation of edge detection and brightness perception." Vision Research 44, no. 16 (July 2004): 1919–25. http://dx.doi.org/10.1016/j.visres.2004.03.005.

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31

Sulutvedt, Unni, Daniele Zavagno, Jamie Lubell, Siri Leknes, Sigrid A. de Rodez Benavent, and Bruno Laeng. "Brightness perception changes related to pupil size." Vision Research 178 (January 2021): 41–47. http://dx.doi.org/10.1016/j.visres.2020.09.004.

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32

Blommaert, Frans J. J., and Jean-Bernard Martens. "An object-oriented model for brightness perception." Spatial Vision 5, no. 1 (1990): 15–41. http://dx.doi.org/10.1163/156856890x00066.

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33

Withouck, Martijn, Kevin A. G. Smet, Wouter R. Ryckaert, Michael R. Pointer, Geert Deconinck, Jan Koenderink, and Peter Hanselaer. "Brightness perception of unrelated self-luminous colors." Journal of the Optical Society of America A 30, no. 6 (May 28, 2013): 1248. http://dx.doi.org/10.1364/josaa.30.001248.

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34

Kobayashi, Yuki, Soyogu Matsushita, and Kazunori Morikawa. "“Glowing Gray” Does Exist: Luminance Gradients’ Influence on Whiteness Perception." Perception 47, no. 7 (May 11, 2018): 772–79. http://dx.doi.org/10.1177/0301006618775238.

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Studies on brightness and lightness that employed luminance gradients (i.e., glare stimuli) have suggested that we can perceive luminosity even when the brightness target is darker than white. Although such studies had great impact on research in luminosity perception, whether the whiteness threshold in glare stimuli was lower or higher than the luminosity threshold remained unclear. This study indicated that it is higher than the luminosity threshold, confirming the existence of glowing gray. Moreover, we measured the luminance gradients’ effect on whiteness perception but found no significant effect. Discrepancy in the degree of gradients’ effect on perceived luminosity and perceived white suggests that different mechanisms underlie luminosity (brightness) perception and whiteness (lightness) perception.

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35

Hu, Kuntao, Ziqi Xu, Xiufang Wang, Yingyu Wang, Haoran Li, and Yibing Zhang. "Research on Street Color Environment Perception Based on CEP-KASS Framework." Buildings 13, no. 10 (October 20, 2023): 2649. http://dx.doi.org/10.3390/buildings13102649.

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The color of urban streets plays a crucial role in shaping a city’s image, enhancing street appeal, and optimizing the experience of citizens. Nevertheless, the relationship between street color environment and residents’ perceptions has rarely been deeply discussed, and most of the existing studies adopt qualitative methods. To accurately and effectively assess the connection between street color environment and residents’ emotional perceptions, this paper introduces a quantitative research framework based on multi-source data called “Color Emotion Perception with K-Means, Adversarial Strategy, SegNet, and SVM (CEP-KASS)”. By combining K-Means unsupervised machine learning and SegNet computer vision techniques, it captures and analyzes visual elements and color data from Baidu Street View Images (BSVI). It then employs a human–machine adversarial scoring model to quantify residents’ perceptions of BSVI and uses the support vector machine regression model to predict the final perception scores. Based on these data, a Pearson correlation analysis and visual analysis were conducted on the elements and color in the urban environment. Subsequently, the streets were classified based on perception frequency and perception scores by integrating multi-source data, and areas within the third ring of Xuzhou City were selected for validating the research framework. The results demonstrate that utilizing street-view images and the CEP-KASS framework can quantitatively analyze urban color perception and establish a connection with residents’ emotions. In terms of color perception, red, orange, and blue all have a strong positive correlation with the interesting score, whereas black is positively correlated with a sense of safety. Regarding color attributes, low-saturation bright colors result in higher fun perception scores in urban spaces; too low saturation and brightness can affect their attractiveness to residents; brightness has an inverse relationship with the perception of safety, and adjusting brightness inversely can improve the perceived safety experience in certain urban external spaces. The street classification criteria based on perception frequency and perception scores proposed herein can provide references for planners to prioritize color transformation decisions, with a priority on emulating HSHF streets and transforming LSHF streets. When formulating color planning, suggestions for color adjustment can be given based on the correlation study of color with visual elements and perception scores, optimizing urban residents’ spatial perception and their emotional experiences. These findings provide robust theoretical support for further enhancing the visual quality of streets and refining urban color planning.

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36

Polischuk, Valentyna, and Oksana Koliada. "Visual Perception in External Lighting Conditions." Lighting Engineering & Power Engineering 60, no. 2 (October 29, 2021): 71–78. http://dx.doi.org/10.33042/2079-424x.2021.60.2.04.

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LED street lighting is a topical trend in modern outdoor lighting. High light output of LEDs creates all conditions for modernization of electric lighting networks in Ukraine. Human vision is a complex process associated with retinal light perception. Vision is divided into: day vision, night vision, and twilight vision. The function of the eye is highly dependent on the distribution of brightness in the field of vision. The spectral sensitivity of photoreceptors varies for different wavelengths of the visible spectrum and different levels of light intensity. The rationing of the lighting installation is based on detailed studies of the observer’s visual performance depending on different lighting conditions. One of the main luminous parameters that can easily be measured objectively is illumination. Brightness as a function of illumination, the observer’s position and the spectral coefficient of the working surface reflection is more informative, but has some difficulty in measuring. There is a clear need to develop a system that would make it possible to uniquely assess the visual efficiency of a given spectral composition under certain observation conditions. It was decided to introduce the term equivalent brightness as the parameter of such a system. The difficulty of using the function Vek(λ,Lek) to calculate the equivalent brightness is the function’s dependence Vek(λ,Lek) on Lek. The aim of the study is to approximate the function of the relative spectral luminous efficiency in mesopathic regions by a set of standard CIE functions that do not depend on the value of equivalent luminosity. The calculation method Vek(λ,Lek) is proposed using only two normalized functions of the relative spectral radiation efficiency for day V(λ) and night V'(λ) vision. The use of such approximation function makes it possible to determine the equivalent brightness, which adequately reflects the level of visual perception under the conditions of ambient illumination, based on the photometric brightness of the light source. To calculate Vek(λ,Lek) we use the ICE recommended functions of relative spectral light efficiency for the twilight vision, which are based on the spectral composition of the blackbody radiation with a color temperature of 2042 K. The use of the developed methodology provides results that more accurately characterize the efficiency of light sources in outdoor lighting installations compared to the results of calculations obtained when using standard methods.

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37

Pracki, Piotr, and Rafał Krupiński. "Brightness and Uniformity Perception of Virtual Corridor with Artificial Lighting Systems." Energies 14, no. 2 (January 13, 2021): 412. http://dx.doi.org/10.3390/en14020412.

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This article compares the brightness and uniformity perception of virtual corridor displayed on computer screens and under different surrounding conditions, between two groups of respondents. The computer simulations of 10 lighting scenarios in the empty corridor, diverse in terms of luminance distribution and lighting power density, were developed. The visual assessment of the lighting effects was carried out on the basis of surveys. The respondents assessed the brightness and uniformity of each plane and entire corridor for each scenario, using semantic differential scaling. Each person from the first group individually made their evaluations on the same computer screen placed in the experimental box. Each person from the second group made the assessments on different computer screens, and all respondents from this group made the evaluations in the computer room at the same time. A high convergence of the results between the groups was found in the assessments of brightness and uniformity perception for consecutive lighting situations. In 93.75% of cases, the same perception in brightness and uniformity between the group means was achieved. A high convergence of the results between the groups in the assessment of brightness and uniformity perception for the same lighting situations was also demonstrated.

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38

Hong, Xin-Chen, Guang-Yu Wang, Jiang Liu, and Emily Dang. "Perceived Loudness Sensitivity Influenced by Brightness in Urban Forests: A Comparison When Eyes Were Opened and Closed." Forests 11, no. 12 (November 24, 2020): 1242. http://dx.doi.org/10.3390/f11121242.

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Soundscape plays a positive, health-related role in urban forests, and there is a competitive allocation of cognitive resources between soundscapes and lightscapes. This study aimed to explore the relationship between perceived loudness sensitivity and brightness in urban forests through eye opening and closure. Questionnaires and measuring equipment were used to gather soundscape and lightscape information at 44 observation sites in urban forested areas. Diurnal variations, Pearson’s correlations, and formula derivations were then used to analyze the relationship between perception sensitivity and how perceived loudness sensitivity was influenced by lightscape. Our results suggested that soundscape variation plays a role in audio–visual perception in urban forests. Our findings also showed a gap in perception sensitivity between loudness and brightness, which conducted two opposite conditions bounded by 1.24 dBA. Furthermore, we found that the effect of brightness on perceived loudness sensitivity was limited if variations of brightness were sequential and weak. This can facilitate the understanding of individual perception to soundscape and lightscape in urban forests when proposing suitable design plans.

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39

Besenecker, UC, and JD Bullough. "Investigating visual mechanisms underlying scene brightness." Lighting Research & Technology 49, no. 1 (August 3, 2016): 16–32. http://dx.doi.org/10.1177/1477153516628168.

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Short-wavelength (<500 nm) output of light sources enhances scene brightness perception in the low-to-moderate photopic range. This appears to be partially explained by a contribution from short-wavelength cones. Recent evidence from experiments on humans suggests that intrinsically photosensitive retinal ganglion cells (ipRGCs) containing the photopigment melanopsin might also contribute to spectral sensitivity for scene brightness perception. An experiment was conducted to investigate this possibility at two different light levels, near 10 lx and near 100 lx. Subjects provided forced-choice brightness judgments and relative brightness magnitude judgments when comparing two different amber-coloured stimuli with similar chromaticities. A provisional brightness metric including an ipRGC contribution was able to predict the data with substantially smaller errors than a metric based on cone input only.

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40

Kanizsa, Gaetano, and Gian Franco Minguzzi. "An Anomalous Brightness Differentiation." Perception 15, no. 2 (April 1986): 223–26. http://dx.doi.org/10.1068/p150223.

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The two adjacent regions of a homogeneous surface divided by a thin line may appear different in brightness. The phenomenon is weak, but can be obtained and systematically studied under certain experimental conditions. Data suggest that the effect is influenced by both the spatial position and the relative size of the two regions. The phenomenon is worthy of further examination because it challenges current theories of brightness perception.

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41

Arrington, Karl Frederick. "Directional Filling-in." Neural Computation 8, no. 2 (February 15, 1996): 300–318. http://dx.doi.org/10.1162/neco.1996.8.2.300.

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The filling-in theory of brightness perception has gained much attention recently owing to the success of vision models. However, the theory and its instantiations have suffered from incorrectly dealing with transitive brightness relations. This paper describes an advance in the filling-in theory that overcomes the problem. The advance is incorporated into the BCS/FCS neural network model, which allows it, for the first time, to account for all of Arend's test stimuli for assessing brightness perception models. The theory also suggests a new teleology for parallel ON- and OFF-channels.

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van de Ven, Vincent, Bert Jans, Rainer Goebel, and Peter De Weerd. "Early Human Visual Cortex Encodes Surface Brightness Induced by Dynamic Context." Journal of Cognitive Neuroscience 24, no. 2 (February 2012): 367–77. http://dx.doi.org/10.1162/jocn_a_00126.

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Visual scene perception owes greatly to surface features such as color and brightness. Yet, early visual cortical areas predominantly encode surface boundaries rather than surface interiors. Whether human early visual cortex may nevertheless carry a small signal relevant for surface perception is a topic of debate. We induced brightness changes in a physically constant surface by temporally modulating the luminance of surrounding surfaces in seven human participants. We found that fMRI activity in the V2 representation of the constant surface was in antiphase to luminance changes of surrounding surfaces (i.e., activity was in-phase with perceived brightness changes). Moreover, the amplitude of the antiphase fMRI activity in V2 predicted the strength of illusory brightness perception. We interpret our findings as evidence for a surface-related signal in early visual cortex and discuss the neural mechanisms that may underlie that signal in concurrence with its possible interaction with the properties of the fMRI signal.

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BREITMEYER, BRUNO G., RALPH ZIEGLER, and GERT HAUSKE. "Central factors contributing to para-contrast modulation of contour and brightness perception." Visual Neuroscience 24, no. 2 (March 2007): 191–96. http://dx.doi.org/10.1017/s0952523807070393.

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Following up on a prior study of contour and brightness processing in visual masking (Breitmeyer et al., 2006), we investigated the effects of a binocular and dichoptic para-contrast masking on the visibility of the contour and brightness of a target presented to the other eye. Combined, the results support the contributions of several cortical processes to para-contrast: (1) two central sources of inhibition, one long-latency and prolonged and the other short-latency and brief; (2) binocular rivalry suppression; and (3) a facilitatory effect peaking at different SOAs for the contour and the brightness tasks, reflecting; (4) known properties of two separate cortical systems, one a fast contour-processing pathway and the other a slower brightness-processing pathway.

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Irikura, T., T. Taniguchi, and Y. Aoki. "Brightness Perception of Light with Ununiform Luminance Distribution." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 77, Appendix (1993): 112–13. http://dx.doi.org/10.2150/jieij1980.77.appendix_112.

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Walker, James T., and Roger D. Saunders. "Form perception: Some effects of brightness and motion." Perception & Psychophysics 38, no. 5 (September 1985): 471–75. http://dx.doi.org/10.3758/bf03207178.

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岡崎, 秀俊, and 宏紀河合. "Illusion Simulation Corresponding to Brightness Perception of Vision." 産業応用工学会論文誌 5, no. 1 (2017): 12–17. http://dx.doi.org/10.12792/jjiiae.5.1.12.

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Bullough, John D. "Spectral Sensitivity Modeling and Nighttime Scene Brightness Perception." LEUKOS 11, no. 1 (November 21, 2014): 11–17. http://dx.doi.org/10.1080/15502724.2014.982820.

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Shapley, R., and R. C. Reid. "Contrast and assimilation in the perception of brightness." Proceedings of the National Academy of Sciences 82, no. 17 (September 1, 1985): 5983–86. http://dx.doi.org/10.1073/pnas.82.17.5983.

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Hung, Chou P., Benjamin M. Ramsden, and Anna Wang Roe. "A functional circuitry for edge-induced brightness perception." Nature Neuroscience 10, no. 9 (August 19, 2007): 1185–90. http://dx.doi.org/10.1038/nn1948.

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Waters, Clarence E., Richard G. Mistrick, and Craig A. Bernecker. "Brightness Perception from Sources of Non-Uniform Luminance." Journal of the Illuminating Engineering Society 27, no. 2 (July 1998): 89–101. http://dx.doi.org/10.1080/00994480.1998.10748237.

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