Incorporating Human Contrast Sensitivity in Model Observers for Detection Tasks

Contrast sensitivity of the human visual system is a characteristic that can adversely affect human performance in detection tasks. In this paper, we propose a method for incorporating human contrast sensitivity in anthropomorphic model observers. In our method, we model human contrast sensitivity using the Barten model with the mean luminance of a region of interest centered at the signal location. In addition, one free parameter is varied to control the effect of the contrast sensitivity on the model observer´s performance. We investigate our model of human contrast sensitivity in a channelized-Hotelling observer (CHO) with difference-of-Gaussian channels. We call the CHO incorporating the contrast sensitivity a contrast-sensitive CHO (CS-CHO). The human data from a psychophysical study by Park are used for comparing the performance of the CS-CHO to human performance. That study used Gaussian signals with six different signal intensities in non-Gaussian lumpy backgrounds. A value of the free parameter is chosen to match the performance of the CS-CHO to the mean human performance only at the strongest signal. Results show that the CS-CHO with the chosen value of the free parameter predicts the mean human performance at the five lower signal intensities. Our results show that the CS-CHO predicts human performance well as a function of signal intensity.