A diagnostic tool for assessing lighting in buildings: investigating luminance contrast relationships through high-dynamic-range image based analysis

This study examines the applicability of high dynamic range (HDR) imagery as a diagnostic tool for studying lighting quality in interior environments. It originates from the limitations in lighting quality assessments, particularly from the problematic nature of measuring luminance contrast--a significant lighting quality definer. In this research, HDR imaging method is studied systematically and in detail via extensive camera calibration tests considering the effect of lens and light source geometry (i.e. vignetting, point spread and modulation transfer functions), in-camera variables (i.e. spectral response, sensor sensitivity, metering mode,), and environmental variables (i.e. ambient light level, surface color and reflectance, light source spectral power distribution) on the accuracy of HDR-image-derived luminance data. The calibration test findings are used to create camera setup and calibration guidelines for future research, especially to help minimize errors in image extracted lighting data. The findings are also utilized to demonstrate the viability of the tool in a real world setting--an office environment combining vertical and horizontal tasks. Via the quasi-experimental setup, the relationship between line of sight and perceived luminance contrast ratios are studied using HDR images. Future research can benefit from the calibration guidelines to minimize HDR-based luminance estimation errors. The proposed tool can be used and tested in different contexts and tasks with varying user groups for revising the former luminance-contrast guidelines as well as surface reflectance recommendations.