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 visu al sensitivity to plumes. The resultant probability of detection algor ithm (PROBDET) allows one to estimate the probability of a plume of kn own size, shape and contrast being detected visually. As a basis for t he algorithm, a series of laboratory experiments using a high threshol d signal detection procedure and computer generated images of plumes w ith Gaussian luminance distributions was conducted to measure human vi sual sensitivity to plumes. Results of the laboratory experiments are compared with results of contrast sensitivity experiments that examine d visual sensitivity to stimuli with square and sine wave luminance di stributions. An example of the PROBDET algorithm is presented to demon strate its potential usefulness for assessing how probability of detec tion estimates change as plume size and contrast parameters vary. Sinc e this research was designed to build on existing knowledge, a discuss ion of that knowledge and how it relates to the research conducted is also presented. The focus of this discussion is on the human visual sy stem (HVS) and on how visual sensitivity is affected by factors such a s the luminance of the stimulus and the surround, the luminance distri bution of the stimulus, the size of the surround, and the size and spa tial frequency characteristics of the stimulus.