Name
Abstract | ||
|---|---|---|
We propose a hybrid contextual fire detection algorithm for airborne and satellite thermal images. The proposed algorithm essentially treats fire pixels as anomalies in images and can be considered a special case of the more general clutter or background suppression problem. It utilizes the local background around a potential fire pixel and discriminates fire pixels based on the squared Mahalanobis distance in multispectral feature space. It also employs the normalized thermal index to identify background fire pixels that should be excluded from the calculation of the statistical properties of the local background. The use of the squared Mahalanobis distance naturally incorporates the covariance of the multispectral image into the decision and requires the setting of a single detection threshold. By contrast, previous contextual algorithms only incorporate the statistical properties of individual bands and require the manual setting of multiple thresholds. Compared with the latest Moderate Resolution Imaging Spectroradiometer fire product (version 4), our algorithm improves user accuracy and producer accuracy by 1.5% and 2.6% on average, respectively, and up to 28% for some images. In addition, the novel use of the squared Mahalanobis distance allows us to create fire probability images that are useful for fire propagation modeling. As an example, we demonstrate this use for the airborne data. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TGRS.2005.853935 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
multispectral feature space,background suppression problem,geophysical techniques,remote sensing,squared mahalanobis distance,image processing,mahalanobis distance,fire probability images,fires,infrared imaging,multi-spectral images,index terms— wildland fire detection,background fire pixels,multispectral images,anomaly detection,satellite thermal images,fire propagation modeling,multispectral imagery,general clutter,airborne thermal images,wildland fire detection,normalized thermal index,moderate resolution imaging spectroradiometer | Computer vision,Anomaly detection,Computer science,Remote sensing,Multispectral image,Mahalanobis distance,Artificial intelligence,Fire detection | Journal |
Volume | Issue | ISSN |
43 | 9 | 0196-2892 |
Citations | PageRank | References |
12 | 3.15 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Li | 1 | 12 | 3.15 |
| Anthony Vodacek | 2 | 119 | 17.07 |
| Robert L. Kremens | 3 | 12 | 4.16 |
| Ambrose E. Ononye | 4 | 18 | 4.83 |
| Chunqiang Tang | 5 | 1287 | 75.09 |