Model-based morphology
Robert M. Haralick, Edward R. Dougherty, Philip L. Katz · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
Filtering by morphological operations is particularly suited for removal of clutter and noise objects which have been introduced into noiseless binary images. The morphological filtering is designed to exploit differences in the spatial nature (shape, size, orientation) of the objects (connected components) in the ideal noiseless images as compared to the noise/clutter objects. Since the typical noise models (union, intersection set difference, etc.) for binary images are not additive, and the morphological processing is strongly nonlinear, optimal filtering results conventionally available for linear processing in the presence of additive noise are not directly applicable to morphological filtering of binary images. In this paper, a morphological filtering analog to the classic Wiener filter is described.