In color gamut mapping of pictorial images, the lightness rendition of the mapped images plays a major role in the quality of the final image. For color gamut mapping tasks, where the goal is to produce a match to the original scene, it is important to maintain the perceived lightness contrast of the original image. Typical lightnessremapping functions such as linear compression, soft compression, and hard clipping reduce the lightness contrast of the input image. Sigmoidal-remapping functions were utilized to overcome the natural loss in perceived lightness contrast that results when an image from a full dynamic range device is scaled into the limited dynamic range of a destination device. These functions were tuned to the particular lightness characteristics of the images used and the selected dynamic ranges. The sigmoidal-remapping functions were selected based on an empirical contrast enhancement model that was developed from the results of a psychophysical adjustment experiment. The results of this study showed that it was possible to maintain the perceived lightness contrast of the images by using sigmoidal contrast enhancement functions to selectively rescale images from a source device with a full dynamic range into a destination device with a limited dynamic range.