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 for reducing pose estimation errors beyond the possibilities of conventional Perspective-n-Point solutions by considering the underlying optimization as a focusing problem. We present an efficient image integration technique, which also reduces the parameter search space to achieve realistic processing times, and improves the quality of resulting synthetic integral images.

Automated summary

In this letter, a new approach is presented for reducing pose estimation errors by considering the underlying optimization as a focusing problem, surpassing conventional solutions. An efficient image integration technique is also introduced to reduce parameter search space and improve the quality of resulting synthetic integral images.