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Proceedings Paper

Optimal binary filters with linearly separable preprocessing
Author(s): Octavian Valeriu Sarca; Edward R. Dougherty; Jaakko T. Astola
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Paper Abstract

The practical issues in the design and implementation of the optimal binary filters limit the observation windows down to a size that is usually much smaller than the characteristic features found in document images. To overcome this drawback, a new composite binary filtering method is developed. A preprocessing stage based on linearly separable Boolean functions is used to gather information from a very large window. The pre-filtering results together with the pixel values from a smaller window are then faded into an optimal estimator. The proposed filter structure can be viewed either as a two stage binary filter with linearly separable preprocessing or as a locally adaptive binary filter where the local adaptation is based on the characteristic features extracted from a large window. Both software and hardware implementations of the filter exhibit reasonable complexity even for large windows. Some properties of the filter and a closed form expression of the mean-absolute-error are derived. It is shown that, because there are no restrictions in the second stage, the whole composite structure can be optimally designed. The paper develops a practical design procedure that uses an efficient gradient method. Computer simulations are used to test the proposed filter against the optimal binary filter.

Paper Details

Date Published: 6 April 1998
PDF: 11 pages
Proc. SPIE 3304, Nonlinear Image Processing IX, (6 April 1998); doi: 10.1117/12.304608
Show Author Affiliations
Octavian Valeriu Sarca, Tampere Univ. of Technology (Finland)
Edward R. Dougherty, Texas A&M Univ. (United States)
Jaakko T. Astola, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 3304:
Nonlinear Image Processing IX
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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