Idempotence and automatic linear contrast enhancements

We investigate the natural requirement that an automated contrast enhancement algorithm be idempotent. We show that in a restricted but natural setting, it leads to a binding of the contrast changes with the decision procedure. We obtain: a natural decision procedure for the standard gamma-transformations; a class of contrast changes generalizing these; a procedure to "learn" an algorithm from a set of good images.