Paper
1 August 1991 Model-based morphology
Author Affiliations +
Abstract
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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert M. Haralick, Edward R. Dougherty, and Philip L. Katz "Model-based morphology", Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); https://doi.org/10.1117/12.46476
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CITATIONS
Cited by 12 scholarly publications.
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KEYWORDS
Image processing

Image filtering

Binary data

Filtering (signal processing)

Image understanding

Americium

Interference (communication)

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