Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization

Indrajit Kurmi, David C. Schedl, Oliver Bimber

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


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.

Original languageEnglish
Article number9086501
Pages (from-to)836-840
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number5
Publication statusPublished - May 2021
Externally publishedYes


  • Enhancement
  • computer vision
  • image processing


Dive into the research topics of 'Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization'. Together they form a unique fingerprint.

Cite this