Abstract
The use of information about an image in addition to measured data has been demonstrated to provide the possibility of decreasing the noise in the measured data. A new constraint, recently proposed, is that of perfect knowledge of part of an image. These results are generalized, and the usefulness of this new constraint in decreasing noise outside the region of prior knowledge is shown to be a function of the measured data noise-correlation properties. In particular, it is shown that prior high-quality knowledge is a generalization of support constraints.
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