A neural response-based model to predict discomfort glare from luminance image

Abstract

It is well known that one of the problems of the current method for discomfort glare evaluation, called the unified glare rating, is the non-uniform luminance of the glare source. This paper addresses this issue by considering the spatial contrast of luminance as a measure of non-uniformity. An image-based metric is proposed to evaluate discomfort glare by modeling the neural response of human vision. The model takes an absolute luminance image as input and predicts visual discomfort based on the spatial distribution of the luminance of the stimulus and the background. The developed model was tested to predict subjective glare ratings based on an experiment conducted using non-uniform LED sources with symmetric and asymmetric patterns of LEDs, and its performance was compared with the unified glare rating. As expected, the unified glare rating predictions correlated well with the subjective glare evaluations of luminaires with symmetric patterns of LEDs (as they appear less non-uniform) but not for those with asymmetric patterns. Results showed that the developed model, named the Neural Response-based Glare Model, gave similar performance to unified glare rating for symmetric patterns but outperformed UGR for asymmetric patterns of LEDs.

Visual Comfort Evaluation Method and Prediction Model Relating to Discomfort Glare: A Mock-Up Study of Luminous Environment in Airplane Cockpit

“…to evaluate visual discomfort. Safdar et al (2018) used the neural computations of the human visual system to model neural responses to glare based on the spatial distribution of luminance , which refers to a model they called neural response-based glare model (NRGM).…”

“…Five parameters of the glare sources, include source luminance, background luminance, position index, solid angle of source, and the vertical illuminance were selected to compute diffe rent discomfort glare indexes include UGR, DGI, and DGP. The NGRM model was also computed, the detailed computation procedure was based on Safdar's work (Safdar et al, 2018). The correlation analysis was implemented to find the relationship between different glare models and the 1-9 1 2 1 2 3 6 5 4 comfort ratings results.…”

Assessing the application of an image color appearance model to basic self‐luminous scenes

“…In 2012, Reinhard et al proposed a calibrated image appearance model used for scene and video reproduction. Some elements from the image‐based approach have also been used in other disciplines of vision research such as for predicting discomfort glare of nonuniform and complex luminaires by introducing the receptive field concept as a kernel …”

“…Some elements from the image-based approach have also been used in other disciplines of vision research such as for predicting discomfort glare of nonuniform and complex luminaires by introducing the receptive field concept as a kernel. 15,16 Among the existing image appearance models, iCAM 11 can be referenced as the standard. This model uses the pixelby-pixel tristimulus values of an image as the input and outputs the perceptual attributes (brightness, hue, colorfulness, lightness, chroma, and saturation) for each pixel of the image.…”

A psychophysical model for visual discomfort based on receptive fields

“…Despite it, the receptive field mechanism, as a physiological link between a luminance distribution and the neural response, becomes increasingly important as an alternative to UGR for the determination of discomfort glare, especially for non-uniform luminaires. [26][27][28] The present study describes a psychophysical model for visual discomfort. The neural response is linked to a luminance distribution by applying the receptive field mechanism on the high resolution luminance map.…”