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):Citrin, Stuart; Azimi-Sadjadi, Mahmood R.Date Issued:1992Format:born digital; articlesA new two-dimensional (2-D) block Kalman filtering method is presented which uses a full-plane image model to generate a more accurate filtered estimate of an image that has been corrupted by additive noise and full-plane ...
Author(s):Azimi-Sadjadi, Mahmood R.Date Issued:1991Format:born digital; articlesThis correspondence is concerned with the development of a recursive identification and estimation procedure for 2-D block Kalman filtering. The recursive identification scheme can be used on-line to update the image model ...
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 ...