Portable, Interoperable, Variable Remapping of Airborne Imagery (VRAI) System

UAV to target-platform handoff requires sufficient correlation between disparate image sensor data to enable visual identification (ID). Differing platform conditions, including aspect and image sensor properties, provide significant variations in imagery, resulting in delays in the chain-of-custody for relocatable targets. SET Corporation proposes to develop a Variable Remapping of Airborne Imagery (VRAI) system to optimally select and transform UAV target imagery to appear as it would from the strike sensor perspective, with respect to target aspect and sensor acquisition conditions, thereby hastening reliable confirmation of targets. The system builds on our Phase I success of demonstrating rapid, reliable, dense novel-view remapping of UAV surveillance video imagery. Both 3D model and homography-based approaches are incorporated to provide rapid, dense remapping under varying image acquisition conditions. Background is remapped to provide enhanced context for verification. Modular development implemented on a COTS PC platform provides for a man-portable system that is interoperable with a variety of UAV and strike platforms. Iterative development based on operator feedback will be employed to ensure robustness for field operation. Operator-based and automated/quantitative evaluation will be performed. The developed, evaluated prototype will be demonstrated and delivered to the Navy.