Where images are displayed such that unintended light is also included and that light cannot be fully subtracted from the displayed image, an image processor compensates by compensating for the remaining light using perceptual models. In some cases, the perceptual model includes a plurality of user sensitivities and computation is performed, at least in part, based on expected user sensitivity to light pollution in portions of the images. The perceptual model might include a contrast sensitivity function, threshold-vs-intensity, saliency prediction and visual masking. The model might include artist indications of view attention. A light pollution likelihood map might be used to reduce the amount of computation needed, using a likelihood measure to determine an amount of computation to perform.