Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization
Computer Vision and Pattern Recognition
2020-05-11 v1 Graphics
Abstract
In this article, 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.
Cite
@article{arxiv.2005.04065,
title = {Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization},
author = {Indrajit Kurmi and David C. Schedl and Oliver Bimber},
journal= {arXiv preprint arXiv:2005.04065},
year = {2020}
}
Comments
5 pages, 4 figures, 1 table, in IEEE Geoscience and Remote Sensing Letters, 2020