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 Pers...
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| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5 |
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| container_title | IEEE geoscience and remote sensing letters |
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| creator | Kurmi, Indrajit Schedl, David C. Bimber, Oliver |
| description | 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. |
| doi_str_mv | 10.1109/LGRS.2021.3051718 |
| format | Article |
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| issn | 1545-598X 1558-0571 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Aperture imaging Cameras Enhancement Error reduction Estimation errors Force Forestry image processing and computer vision Image quality Imaging techniques Optical sectioning Optical sensors Optimization Pose estimation Sectioning Synthetic apertures Thermal sensors |
| title | Pose Error Reduction for Focus Enhancement in Thermal Synthetic Aperture Visualization |
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