Nonlinear filtering structure for smoothing discontinuous signals corrupted with Gaussian noise

Robert L. Stevenson

doi:10.1117/12.58378

1 April 1992 Nonlinear filtering structure for smoothing discontinuous signals corrupted with Gaussian noise

Robert L. Stevenson

Proceedings Volume 1658, Nonlinear Image Processing III; (1992) https://doi.org/10.1117/12.58378
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States

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.

Citation Download Citation

Robert L. Stevenson "Nonlinear filtering structure for smoothing discontinuous signals corrupted with Gaussian noise", Proc. SPIE 1658, Nonlinear Image Processing III, (1 April 1992); https://doi.org/10.1117/12.58378

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