The evaluation of the spatial luminance coefficient, Feu, and average luminance, Lav, can improve the lighting quality from both subjective and objective aspects. In the design survey, the determination of these indicators relies on the manual sampling of the luminance of measurement points, which is time-consuming and labour-intensive. This article proposes a grayscale−luminance converting polynomial function, and a method for the determination of Feu and Lav from digital images via the function. The acceptability index, Nallow, is created as the key parameter of the polynomial function, which reduces the number of required measurement points to 9. Taking visual comfort as the criterion, three types of low-contrast working conditions with different luminance distributions – namely an actual scene, simulated scenes and experimental scenes – were set, the luminance ratios of which were less than 100 and the luminance of which was less than 1000 cd/m2. To minimise the error to within 10%, the piecewise function of Nallow determined by the luminance ratio was constructed, which is obtained via the data verification and correction of 20 working conditions. The experimental results of a test scene demonstrate that the accuracies of Feu and Lav produced by the proposed polynomial function were better than those produced by an exponential function.
Changing the spatial luminance distribution patterns has the potential to improve the restorative potential of indoor environments through spatial visual perception intervention, which is helpful to meet our growing need for psychological restoration and well-being. However, the efficiency, progress, and principles for improving the spatial luminance distribution of indoor environments have not been verified, and the reusable and restorative spatial luminance distribution patterns that can be applied to the restorative reserve levels created by the architectural configurations and dispositions of the different spaces have yet to be established. Using a living room environment as the typical space and a hotel room as the research subject, we conducted this study by setting up a control group for the assessment experiment, combining three subjective and objective measures: the Perceived Restorativeness Scale (PRS), the eye-movement test, and the case interview. The results showed the following. (1) The spatial luminance distribution of artificial lighting can improve the PRS score by 30.9%. (2) The spatial luminance distribution of artificial lighting improves the restorative perception potential, which negatively correlates with the restorative reserve level of the environment (the correlation coefficient values were −0.405, p < 0.01). (3) The spatial luminance distribution elicited two visual cognitive responses: visual attraction and visual load, with the former being positively correlated with restorative perception (the correlation coefficient values were 0.288, p < 0.01), while the latter was negatively correlated (the correlation coefficient values were −0.264, p < 0.01). (4) The visual cognitive conclusions of spatial luminance distribution including the six dimensions present the visual characteristics of the status quo in the restorative spatial luminance distribution of artificial lighting. Based on the findings, this study starts from the optimization of visual attraction and visual load by improving both the restorative level and the degree of restorative perception, proposing a restorative spatial luminance distribution pattern of artificial lighting applicable to environments with different restorative reserve levels.
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