Two-dimensional recursive parameter identification for adaptive Kalman filtering
Date
1991
Authors
Azimi-Sadjadi, Mahmood R., author
Bannour, Sami, author
IEEE, publisher
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Abstract
This paper is concerned with the development of a 2-D adaptive Kalman filtering by recursive adjustment of the parameters of an autoregressive (AR) image model with non symmetric half-plane (NSHP) region of support. The image and degradation models are formulated in a 2-D state-space model, for which the relevant 2-D Kalman filtering equations are given. The recursive parameter identification is achieved using the extension of the stochastic Newton approach to the 2-D case. This process can be implemented on-line to estimate the image model parameters based upon the local statistics in every processing window. Simulation results for removing an additive noise from a degraded image are also presented.
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Subject
two-dimensional digital filters
adaptive filters
parameter estimation
picture processing
state-space methods
Kalman filters
filtering and prediction theory