Two-dimensional recursive parameter identification for adaptive Kalman filtering
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 ...
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Azimi-Sadjadi, Mahmood R.; Bannour, Sami
born digital; articles
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Author(s):Pan, Hongye; Azimi-Sadjadi, Mahmood R.Date Issued:1994Format:born digital; articlesThis paper is concerned with the development of a two-dimensional (2-D) adaptive filters using the block diagonal least mean squared (BDLMS) method. In this adaptive filtering scheme the image is scanned and processed block ...
Author(s):Nebot, Eduardo Mario; Lu, Tongxin; Azimi-Sadjadi, Mahmood R.Date Issued:1991Format:born digital; articlesTwo sets of block Kalman filtering equations are derived that differ in the manner of generating the initial and updated estimates. Parallel and sequential schemes for generating these estimates are adopted. It is shown ...
Author(s):Azimi-Sadjadi, Mahmood R.; King, Robert A.Date Issued:1987Format:born digital; articlesFor two-dimensional (2-D) digital filters implemented by a block recursive equation, explicit relations between their frequency characteristics and those of scalar filter are obtained. Specifically, these include the ...