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Abstract
A pattern theoretic model of random shape is described and applied to noisy digital images of human hand. Algorithms are derived from the model for processing the pictures, in particular for image restoration. To learn about the power and limitations of the techniques we introduce more and more complex visual noise until the algorithms fail. The noise model is then modified in order to compensate for the peculiarities of the noise. In order to make the techniques computationally feasible analytical results have been exploited to speed up stochastic relaxation.
For massive mathematical experiments on the computer, such as the present one, the mathematician needs more advanced computer resources than are usually available. The need for this is emphasized, in particular for powerful single user machines, and appropriate support personnel
∗Supported by The National Science Foundation Contract No. DMS 8602038, the Army Research Office Contract No. DAAG-29-83-K-0116 and the Office of Naval Research Contract No. N00014-87-K-0367
∗∗For figures 1,3,4,6, and 8, see color inserts
∗Supported by The National Science Foundation Contract No. DMS 8602038, the Army Research Office Contract No. DAAG-29-83-K-0116 and the Office of Naval Research Contract No. N00014-87-K-0367
∗∗For figures 1,3,4,6, and 8, see color inserts
Notes
∗Supported by The National Science Foundation Contract No. DMS 8602038, the Army Research Office Contract No. DAAG-29-83-K-0116 and the Office of Naval Research Contract No. N00014-87-K-0367
∗∗For figures 1,3,4,6, and 8, see color inserts