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
类别
资金
- Austrian Science Fund (FWF) [P 32185-NBL]
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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