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Proceedings Paper

Conditional-expectation-based implementation of the optimal mean-square binary morphological filter
Author(s): Edward R. Dougherty; Athimootil V. Mathew; Vivek Swarnakar
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Paper Abstract

Even in the binary case, designing optimal morphological filters involves a time-consuming search procedure that, in practice, can be intractable. The present paper provides an algorithm for filter design that is based upon the relationship between the optimal morphological filter and the conditional expectation. In effect, the algorithm proceeds by changing the conditional expectation into a morphological filter while at the same time increasing the mean-square error a minimal amount. Under many noise environments, the new algorithm is extremely efficient, thereby providing a filter design that can be used online for structuring-element updating.

Paper Details

Date Published: 1 April 1991
PDF: 11 pages
Proc. SPIE 1451, Nonlinear Image Processing II, (1 April 1991); doi: 10.1117/12.44321
Show Author Affiliations
Edward R. Dougherty, Rochester Institute of Technology (United States)
Athimootil V. Mathew, Rochester Institute of Technology (United States)
Vivek Swarnakar, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1451:
Nonlinear Image Processing II
Edward R. Dougherty; Gonzalo R. Arce; Charles G. Boncelet Jr., Editor(s)

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