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Proceedings Paper

Nonlinear filtering structure for smoothing discontinuous signals corrupted with Gaussian noise
Author(s): Robert L. Stevenson
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Paper Abstract

This paper proposes a new nonlinear filtering structure based on a maximum a posteriori estimation criteria using a Markov random field model for the prior distribution. Estimates obtained with the proposed Markov random field model allow discontinuities in the signal to be accurately estimated while additive Gaussian noise is smoothed. A Markov random field based prior is chosen such that the filter has desirable analytical and computational properties. The estimate of the signal value is obtained at the unique minimum of the a posteriori log likelihood function. This function is convex so that the output of the filter can be easily computed using either digital or analog computational methods. Example outputs under various conditions are given.

Paper Details

Date Published: 1 April 1992
PDF: 12 pages
Proc. SPIE 1658, Nonlinear Image Processing III, (1 April 1992); doi: 10.1117/12.58378
Show Author Affiliations
Robert L. Stevenson, Univ. of Notre Dame (United States)

Published in SPIE Proceedings Vol. 1658:
Nonlinear Image Processing III
Edward R. Dougherty; Jaakko T. Astola; Charles G. Boncelet Jr., Editor(s)

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