A Tone Mapping Operator for Road Visibility Experiments
Résumé
One may wish to use computer graphic images to carry out road visibility studies. Unfortunatly, most display devices still have a limited luminance dynamic range, especially in driving simulators. In this paper, we propose a Tone Mapping Operator (TMO) to compress the luminance dynamic range while preserving the driver's performance for a visual task relevant for a driving situation. We address 3 display issues of some consequences for road image display: luminance dynamics, image quantization, and high minimum displayable luminance. Our TMO characterizes the effects of local adaptation with a bandpass decomposition of the image using a Laplacian pyramid, and processes the levels separately in order to mimic the Human Visual System. The contrast perception model uses the Visibility Level, a usual index in road visibility engineering applications. To assess our algorithm, a psychophysical experiment devoted to a target detection task was designed. Using a Landolt ring, the visual performances of 30 observers were measured: they stared first at a High Dynamic Range image, then at the same image processed by a TMO and displayed on a Low Dynamic Range monitor, for comparison. The evaluation was completed with a visual appearance evaluation. Our operator gives good performances for 3 typical road situations (one in daylight, two at night), after comparison with 4 standard TMOs from the literature. The psychovisual assessment of our TMO is limited to these driving situations.