Paper
21 May 1993 Optimal single-stage restoration of subtractive noise
Larry R. Rystrom, Robert M. Haralick, Philip L. Katz
Author Affiliations +
Proceedings Volume 1902, Nonlinear Image Processing IV; (1993) https://doi.org/10.1117/12.144754
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States
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.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Larry R. Rystrom, Robert M. Haralick, and Philip L. Katz "Optimal single-stage restoration of subtractive noise", Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); https://doi.org/10.1117/12.144754
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KEYWORDS
Nonlinear image processing

Image processing

Binary data

Distance measurement

Image restoration

Applied physics

Image filtering

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