Stochastic sampling has proven to be an effective means of reducing many types of aliasing artifacts. However, stochastic sampling requires many samples in order to produce images which appear free of noise, especially when used to antialias procedural textures or the shadowing effects of area light sources. This paper describes an algorithm to improve the signal to noise ratio of stochastically sampled images by averaging pixel intensity information from several frames. The algorithm can be applied to the types of shading models typically used in scanline Z-buffer renderers or in ray tracers. The algorithm predicts the motion of pixels in screen space, effectively compensating out the effect of motion in the scene. The new algorithm has several attractive characteristics. It is efficiently applied as a post process or as an adjunct to an existing renderer. In either case, the extra computation required for the motion prediction is small compared to the time required to render the original image and the improvements in signal to noise ratio can be substantial.