Abstract
Detecting camouflaged targets in an unknown environment presents a great challenge in hyperspectral image analysis since the prior knowledge about targets and background is not available. A nomaly detection method for hyperspectral imagery was proposed for this problem. Features were extracted from subband sets of hyperspectral imagery, then fusion algorithm for detection was implemented by D-S evidence reasoning while basic belief assignment function was constructed involving high-order moments of features. Theoretical analysis and results of experiment verify the effectiveness of the algorithm.
Original language | English |
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Pages (from-to) | 1752-1755 |
Number of pages | 4 |
Journal | Guangzi Xuebao/Acta Photonica Sinica |
Volume | 34 |
Issue number | 11 |
State | Published - Nov 2005 |
Keywords
- Band subsets
- Evidence reasoning
- Feature fusion
- Hyperspectral imagery processing
- Target detection