Psychovisual Perception Scale Based on a Neural Network

Abstract

The purpose of this article is to construct a psychophysical scale of visual perception from lighting scene based on a direct propagation neural network using for assessment of real or synthesized images with spatial brightness distribution. Visual perception assessments of different scenes were obtained for 10 observers at the experimental installation of the Department of lighting engineering of the MPEI (NRU). These results were checked and found out agreed with the numerical scale of visual perception proposed by Lekish and Holladay. Neural network was trained to predict a sensation at the level of 40-70%, depending on the scale category. For more careful prediction level in each of 5 categories of scale a new experiment should be done with new calibration and with tested instructions and with more observers involved. The novelty consists in using a neural network as an expert to assess the degree of comfort of the lighting scene.