In the absence of a priori information on scales of interest vision systems should initially process in a scale invariant manner. The fact that any signal can only be sampled discretely further constrains the initial processing. The paper argues that a representation satisfying these requirements is an hierarchical segmentation of scalespace. An algorithm is presented to compute such representations. The algorithm has been designed so that its operation is scale invariant in the following sense: the addition of finer scale information only ever adds to the computed representation and never changes what was discoverable from coarser scales. It is noted that such a scheme has benefits even when the scales of interest are known.