Title :
A fast recursive two-dimensional estimation algorithm
Author :
Celebi, Mehmet E. ; Kurz, Ludwik
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Polytech. Univ., Brooklyn, NY, USA
Abstract :
A two-dimensional Kalman filtering scheme based on the Roesser local state-space model is given. This algorithm does not provide the conditional mean with respect to previously scanned data; rather, it generates the best gain sequence with respect to local data and prediction. This procedure is also compared experimentally to an optimal filter on noisy images, and it is observed that similar performances in terms of minimum mean square error and an enormous reduction in computations are obtained
Keywords :
Kalman filters; computerised picture processing; estimation theory; filtering and prediction theory; recursive functions; state-space methods; Roesser local state-space model; best gain sequence; computation time; fast recursive two-dimensional estimation algorithm; minimum mean square error; noisy images; two-dimensional Kalman filtering scheme; Autocorrelation; Equations; Kalman filters; Predictive models; Recursive estimation; State estimation; Virtual manufacturing; White noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.151020
