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Proceedings Paper

Optimal single-stage restoration of subtractive noise
Author(s): Larry R. Rystrom; Robert M. Haralick; Philip L. Katz
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Paper Abstract

This paper analyzes restoration of subtractive noise on a binary image by a single morphological operation, dilation. Restoration by dilation alone is appropriate under particular explicitly defined random noise models, based respectively on erosion, independent pixel subtractive noise, and independent pixel subtractive noise followed by dilation. Since in general it is not possible to perfectly restore subtractive noise we use the Hausdorf metric to measure the residual error in restoration. This metric is the appropriate one because of its geometric interpretation in terms of set coverings. We describe a search procedure to find a structuring element for dilation that is optimal in the sense of minimizing the mean Hausdorf error. The search procedure's utility function is based on the calculation of certain probabilities related to the noise model, namely the probability of one set being the subset of another set and some related probabilities.

Paper Details

Date Published: 21 May 1993
PDF: 12 pages
Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); doi: 10.1117/12.144754
Show Author Affiliations
Larry R. Rystrom, Univ. of Washington (United States)
Robert M. Haralick, Univ. of Washington (United States)
Philip L. Katz, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 1902:
Nonlinear Image Processing IV
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham, Editor(s)

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