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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhou, L. Kambhamettu, C. Goldgof, D.B. |
| Copyright Year | 2000 |
| Description | Author affiliation: Dept. of Comput. & Inf. Sci., Delaware Univ., Newark, DE, USA (Zhou, L.) |
| Abstract | We present a novel approach to estimate and analyze 3D fluid structure and motion of clouds from multi-spectrum 2D cloud image sequences. Accurate cloud-top structure and motion are very important for a host of meteorological and climate applications. However, due to the extremely complex nature of cloud fluid motion, classical nonrigid motion analysis methods are insufficient for solving this particular problem. In this paper, two spectra of satellite cloud images are utilized. The high-resolution visible channel is first used to perform cloud tracking by using a recursive algorithm which integrates local motion analysis with a set of global fluid constraints, defined according to the physical fluid dynamics. Then, the infrared channel (thermodynamic information) is incorporated to post-process the cloud tracking results in order to capture the cloud density variations and small details of cloud fluidity. Experimental results on GOES (Geostationary Operational Environmental Satellite) cloud image sequences are presented in order to validate and evaluate both the effectiveness and robustness of our algorithm. |
| Starting Page | 744 |
| Ending Page | 751 |
| File Size | 722504 |
| Page Count | 8 |
| File Format | |
| ISBN | 0769506623 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2000.854949 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-06-15 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Motion analysis Clouds Image sequences Satellites Motion estimation Image analysis Image motion analysis Image sequence analysis Meteorology Tracking |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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