Pose Error Reduction for Focus Enhancement in Thermal Synthetic Aperture Visualization

• URL: http://arxiv.org/abs/2012.08606v1
• Date: Tue, 15 Dec 2020 20:43:46 GMT
• Title: Pose Error Reduction for Focus Enhancement in Thermal Synthetic Aperture Visualization
• Authors: Indrajit Kurmi, David C. Schedl, and Oliver Bimber
• Abstract summary: We present a new approach for reducing pose estimation errors 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.
• Score: 1.8352113484137622
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Airborne optical sectioning, an effective aerial synthetic aperture imaging technique for revealing artifacts occluded by forests, requires precise measurements of drone poses. In this article 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.

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