A computer implemented method of image generation that employs adaptive, progressive, perception-based spatio-temporal importance sampling to reduce the cost of image generation. The method uses an adaptive approach to sampling which employs refinement criteria based on specific spatio-temporal limits of human vision. By using these refinement criteria the method produces an image with a spatio-temporal structure that is closely matched to the spatio-temporal limits of human vision. Using one sampling criteria the spatial sampling density is adjusted in proportion to the sampled region's exposure duration in a manner that substantially reflects the visual systems's increase in acuity as a function of exposure time. Using other criteria the spatial and temporal sampling frequencies of a region of the image stream are adjusted based on the measured or estimated retinal velocity of the sampled element in a manner that substantially reflects both dynamic visual acuity limits of vision and the critical temporal sampling frequency for the perception of smooth motion. The method includes image parallel, shared-memory multiprocessor implementations based on sample reprojection and primitive reprojection, the latter using a technique of adaptive rasterization. In these implementations the natural temporal image coherence and temporal visibility coherence of the image stream produce a temporal locality of data reference that enhances performance of the system. Because temporal image coherence and temporal visibility coherence increase the spatial resolving performance of the human visual system, the performance of the present method parallels the performance of human vision making performance degradations relatively invisible to the user.