Hole spectrum: model-based optimization of morphological filters

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Abstract
An image representation is developed that is useful for designing optimal morphological filters to restore images suffering from degradation due to subtractive noise. The image and noise models are predicated on the existence of some class of shape primitives into which both image and noise can be decomposed (relative to union). Both deterministic and nondeterministic cases are considered, and in each case the relevant model constraints are fully discussed. The type of filters that are naturally compatible with the image-noise models are analyzed, and the relation to general mean-square morphological optimization is explored.

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