A 2-D adaptive diagonal block Kalman filter for nonsymmetric half plane image models
- 13 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1528-1531
- https://doi.org/10.1109/iscas.1989.100649
Abstract
A 2-D diagonal block recursive representation for 2-D autoregressive (AR) image models with nonsymmetric half-plane (NSHP) regions of support that does not have noncausality problems is introduced. The relevant 2-D block Kalman filter equations are used to obtain suboptimal block filtered estimates for the blurred and noisy image. A recursive parameter identification scheme can be used online to update the model parameters at each processing window suggested. Simulation results are presented.Keywords
This publication has 6 references indexed in Scilit:
- Two-dimensional block implementation of symmetric half-plane recursive digital filtersIEEE Transactions on Circuits and Systems, 1988
- Two-dimensional block Kalman filtering for image restorationIEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
- Block implementation of half-plane digital filtersIEEE Transactions on Circuits and Systems, 1987
- Two-dimensional linear prediction models--part I: Spectral factorization and realizationIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
- Block implementation of two-dimensional digital filtersJournal of the Franklin Institute, 1983
- Kalman filtering in two dimensionsIEEE Transactions on Information Theory, 1977