Human visual sensitivity to plumes with a Gaussian luminance distribution: experiments to develop an empirical probability of detection model

This paper discusses results of a research project designed to develop an empirical model that could be used as a tool to predict human visual sensitivity to plumes. The resultant probability of detection algorithm (PROBDET) allows one to estimate the probability of a plume of known size, shape and contrast being detected visually. As a basis for the algorithm, a series of laboratory experiments using a high threshold signal detection procedure and computer generated images of plumes with Gaussian luminance distributions was conducted to measure human visual sensitivity to plumes. Results of the laboratory experiments are compared with results of contrast sensitivity experiments that examined visual sensitivity to stimuli with square and sine wave luminance distributions. An example of the PROBDET algorithm is presented to demonstrate its potential usefulness for assessing how probability of detection estimates change as plume size and contrast parameters vary. Since this research was designed to build on existing knowledge, a discussion of that knowledge and how it relates to the research conducted is also presented. The focus of this discussion is on the human visual system (HVS) and on how visual sensitivity is affected by factors such as the luminance of the stimulus and the surround, the luminance distribution of the stimulus, the size of the surround, and the size and spatial frequency characteristics of the stimulus.