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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bruno, M.G.S. Moura, J.M.F. |
| Copyright Year | 2000 |
| Description | Author affiliation: Electr. Eng. Dept., Sao Paulo Univ., Brazil (Bruno, M.G.S.) |
| Abstract | We present a Bayesian algorithm for optimal multiframe detection and tracking of small extended targets in two-dimensional (2D) finite resolution images. The algorithm integrates detection and tracking into a single framework using as data a sequence of cluttered sensor snapshots. Performance studies using Monte Carlo simulations show substantial improvements when the proposed Bayes tracker is compared to the association of a correlation filter and a linearized Kalman-Bucy filter. Likewise, there are significant detection performance gains of up to 6 dB in peak signal-to-noise ratio (PSNR) when the multiframe Bayes detector is compared to a single frame likelihood ratio test (LRT) detector. |
| Starting Page | 3192 |
| Ending Page | 3195 |
| File Size | 432509 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780362934 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2000.861216 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-06-05 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Digital images Target tracking Filters PSNR Bayesian methods Image resolution Performance gain Detectors Testing Light rail systems |
| Content Type | Text |
| Resource Type | Article |
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