Heterogeneous Vision Data Fusion for Independently Moving Cameras
Final technical rept. Mar-Sep 2009
TENNESSEE STATE UNIV NASHVILLE
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Image fusion problems can be classified into two categories. In Category-I, images obtained by sensors operating at different wavelengths and viewing a common scene simultaneously are fused. In Category-II, images collected by multiple homogenous andor heterogeneous sensors mounted at different locations, viewing different scenes with partial overlapping, are fused. Category-II image fusion is of high importance for real-time target detection, tracking, and identification over a large terrain. The goal of the project is to investigate and evaluate the existing image fusion algorithms, develop new real-time algorithms for Category-II image fusion, and apply these algorithms in moving target detection and tracking. The research objectives are three-fold image fusion algorithm investigation, new algorithm development, and application of the proposed algorithms to moving target detection and classification.
- Numerical Mathematics
- Target Direction, Range and Position Finding