4.7 Article

Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization

期刊

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 18, 期 5, 页码 836-840

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2020.2987471

关键词

Optimization; Measurement; Forestry; Visualization; Linear programming; Cameras; Apertures; Enhancement; image processing; computer vision

资金

  1. Austrian Science Fund (FWF) [P 32185-NBL]

向作者/读者索取更多资源

The letter discusses the first fully automatic parameter optimization for thermal synthetic aperture visualization, replacing manual exploration of the parameter space. It proves that the visibility of targets in thermal integral images is proportional to the variance of the targets' image, serving as a suitable objective function for optimization. These findings could potentially enable fully autonomous search and rescue operations with camera drones.
In this letter, we describe and validate the first fully automatic parameter optimization for thermal synthetic aperture visualization. It replaces previous manual exploration of the parameter space, which is time-consuming and error-prone. We prove that the visibility of targets in thermal integral images is proportional to the variance of the targets' image. Since this is invariant to occlusion, it represents a suitable objective function for optimization. Our findings have the potential to enable fully autonomous search and recuse operations with camera drones.

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