Morphological scale-space preserving transforms in many dimensions

The theory of an image decomposition that we refer to as a sieve is developed for images defined in any finite number of dimensions. The decomposition has many desirable properties in- cluding the preservation of scale-space causality and the localiza- tion of sharp-edged objects in the transformation domain. The de- composition has the additional properties of manipulability, which means that it is easy to construct pattern recognition systems, and scale-calibration, which means that it may be used for accurate measurement. © 1996 SPIE and IS&T.

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