Multi-region contrast method - A new framework for post-processing HDRI luminance information for visual discomfort analysis

Occupants’ visual comfort is an important consideration in sustainable building design. To help create visually comfortable environments, building designers need an easy-to-use method to predict visual discomfort through simulations. This paper aims to present a proof-of-concept predictive method that analyses the contrast ratios of multi-region luminance-based images. Grasshopper and Radiance were used to develop an analysis algorithm that examines per-pixel luminance values of a high-resolution, 180-degree fisheye High Dynamic Range image (HDRi) and represents the luminance information at different (lower) resolutions relative to the average luminance value of the task. The proposed framework succeeded in reducing the complexity of the data by segmenting the HDR image into lower resolution without compromising the minimum luminance detail needed to identify the main glare sources. Illustrating the luminance distribution pattern of the visual field in lower resolutions opens opportunities in simplified data analysis and the visual communication of luminous conditions. Preliminary analysis suggest that this multi-region contrast method could be used as a simple and fast glare source detection method. This method will be further developed and validated using field data, then it will be published as a tool for practical application by building designers in the near future.