This paper develops a methodology for finding which features in a noisy image are strong enough to be distinguished from background noise. It is based on scale space, i.e. a family of smooths of the image. Pixel locations having statistically significant gradient and/or curvature are highlighted by colored symbols. The gradient version is enhanced by displaying regions of significance with streamlines. Ideas are illustrated with simulated and real images.