Multi-parametric data fusion for enhanced object identification and discrimination
Stephen A. Kupiec, Vladimir B. Markov, Joseph C. Chavez · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
Effective fusion of multi-parametric heterogeneous data is essential for better object identification, characterization and discrimination. In this report we discuss a practical example of fusing the data provided by imaging and nonimaging electro-optic sensors. The proposed approach allows the processing, integration and interpretation of such data streams from the sensors. Practical examples of improved accuracy in discriminating similar but non-identical objects are presented.