A novel divergence measure in Dempster-Shafer evidence theory based on pignistic probability transform and its application in multi-sensor data fusion.
Shijun XuYi HouXinpu DengPeibo ChenKewei OuyangYe ZhangPublished in: Int. J. Distributed Sens. Networks (2021)
Keyphrases
- multi sensor data fusion
- data fusion
- divergence measure
- dempster shafer evidence theory
- kullback leibler
- information fusion
- fusion algorithm
- cross entropy
- mutual information
- belief functions
- combination rule
- evidence theory
- multi sensor
- dempster shafer theory
- probability models
- fuzzy c means
- conditional probabilities
- probability distribution
- distance measure
- artificial intelligence
- image fusion
- posterior probability
- image registration
- feature selection