Optimal binary filters with linearly separable preprocessing

Octavian Valeriu Sarca; Edward R. Dougherty; Jaakko T. Astola

doi:10.1117/12.304608

6 April 1998 Optimal binary filters with linearly separable preprocessing

Octavian Valeriu Sarca, Edward R. Dougherty, Jaakko T. Astola

Proceedings Volume 3304, Nonlinear Image Processing IX; (1998) https://doi.org/10.1117/12.304608
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

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.

Citation Download Citation

Octavian Valeriu Sarca, Edward R. Dougherty, and Jaakko T. Astola "Optimal binary filters with linearly separable preprocessing", Proc. SPIE 3304, Nonlinear Image Processing IX, (6 April 1998); https://doi.org/10.1117/12.304608

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