Case studies of a camera-aided imaging method for evaluation of interior luminous environments

Abstract

This paper introduces a camera-aided imaging method to help lighting practitioners, especially students and beginners, to evaluate the quality of interior luminous environments. This imaging method adopts the high dynamic range photography to acquire millions of luminance values across an interior luminous environment, stores the data on a high dynamic range (HDR) image, and then uses a MatLab code ( http://people.ku.edu/∼h717c996/research.html ) to plot two-dimensional luminance and luminance gradient maps of the luminous environment for further evaluation. Four case studies were conducted to validate this imaging method. The HDR image of each test scenario and its luminance and luminance gradient maps were analysed to evaluate the lighting quality in light of four visual concepts, including hierarchy of focal accents, glare and reflectance, entry of daylight, and lighting the walls. Information extracted from those images could be used to improve problematic lighting conditions. The method is useful for vision-based lighting evaluation practice.