{"title":"A Model for Evaluating the Visual Perception of an Arbitrary Distribution of Luminance in Indoor Lighting Installations","authors":"Vladimir P. Budak, Ekaterina I. Ilyina","doi":"10.33383/2022-108","DOIUrl":null,"url":null,"abstract":"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 %.","PeriodicalId":49907,"journal":{"name":"Light & Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.3000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Light & Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33383/2022-108","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
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 %.
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