Two-dimensional recursive parameter identification for adaptive Kalman filtering Azmim-Sadjadi, Mahmood R. ; Bannour, Sami 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. Colorado State University. Libraries 1991 text ; image application/pdf ECEmra00029.pdf FACFECEN100509ARTI eng c1991 IEEE
Two-dimensional recursive parameter identification for adaptive Kalman filtering
Azmim-Sadjadi, Mahmood R. ; Bannour, Sami
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.
Colorado State University. Libraries
1991
text ; image
application/pdf
ECEmra00029.pdf
FACFECEN100509ARTI
eng
c1991 IEEE