Abstract
In this paper, a recursive model-based algorithm for obtaining the maximum a posteriori (MAP) estimate of the displacement vector field (DVF) from successive image frames of an image sequence is presented. To model the DVF, we develop a nonstationary vector field model called the vector coupled Gauss-Markov (VCGM) model. The VCGM model consists of two levels: an upper level, which is made up of several submodels with various characteristics, and a lower level or line process, which governs the transitions between the submodels. A detailed line process is proposed. The VCGM model is well suited for estimating the DVF since the resulting estimates preserve the boundaries between the differently moving areas in an image sequence. A Kalman type estimator results, followed by a decision criterion for choosing the appropriate line process. Several experiments demonstrate the superior performance of the proposed algorithm with respect to prediction error, interpolation error, and robustness to noise.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 416-429 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Image Processing |
| Volume | 4 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 1995 |
Funding
Manuscript received June 9. 1992; revised January 19, 1994. This work was supported by NATO grant 0103/88. The associate editor coordinating the review of this paper and approving it for publication was Dr. Homer H. Chen. The authors are with the Department of Electrical Engineering and Com-puter Science, McCormick School of Engineering and Applied Science. Northwestern University. Evanston, IL 60208-31I 8 LJSA. IEEE Log Number 9409274.
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design