Optimal binary filters with linearly separable preprocessing Conference Paper uri icon

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.

name of conference

  • Nonlinear Image Processing IX

published proceedings

  • Proceedings of SPIE

author list (cited authors)

  • Sarca, O. V., Dougherty, E. R., & Astola, J. T.

citation count

  • 0

complete list of authors

  • Sarca, Octavian V||Dougherty, Edward R||Astola, Jaakko T

editor list (cited editors)

  • Dougherty, E. R., & Astola, J. T.

publication date

  • April 1998