Pose Error Reduction for Focus Enhancement in Thermal Synthetic Aperture Visualization

Airborne optical sectioning, an effective aerial synthetic aperture imaging technique for revealing artifacts occluded by forests, requires precise measurements of drone poses. In this letter, we present a new approach reducing pose estimation errors beyond the possibilities conventional Perspective-n-Point solutions considering underlying optimization as focusing problem. We efficient image integration technique, which also reduces parameter search space to achieve realistic processing times, and improves quality resulting integral images.