Name
Abstract | ||
|---|---|---|
The approximate Kalman filtering algorithm presented previously (see ibid., vol.3, p.773-88, Nov. 1994) for image sequence processing can introduce unacceptable negative eigenvalues in the information matrix and can have degraded performance in some applications. The improved algorithm presented in this note guarantees a positive definite information matrix, leading to more stable filter performance |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/83.913601 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
covariance matrix,image reconstruction,positive definite,satellites,information matrix,sparse matrices,interpolation,kalman filter,space time,kalman filters,eigenvalues | Alpha beta filter,Interpolation,Artificial intelligence,Ensemble Kalman filter,Invariant extended Kalman filter,Eigenvalues and eigenvectors,Computer vision,Extended Kalman filter,Mathematical optimization,Fast Kalman filter,Algorithm,Kalman filter,Mathematics | Journal |
Volume | Issue | ISSN |
10 | 4 | 1057-7149 |
Citations | PageRank | References |
3 | 0.68 | 2 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Toshio Mike Chin | 1 | 3 | 0.68 |