Temporal fusion for de-noising of RGB video received from small UAVs

Amber D. Fischer; Kyle J. Hildebrand

doi:10.1117/12.851810

26 April 2010 Temporal fusion for de-noising of RGB video received from small UAVs

Amber D. Fischer, Kyle J. Hildebrand

Proceedings Volume 7668, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII; 76680V (2010) https://doi.org/10.1117/12.851810
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Monitoring video data sources received from UAVs is especially challenging because of the quality of the video received. Due to the individual characteristics of the unmanned platform and the changing environment, the important elements in the scene are not always observable or easily identified. In addition to typical sensor noise, significant image degradation can occur during transmission of the video from an airborne platform. Interference from other transmitters, analog noise in the embedded avionics, and multi-path effects can corrupt the video signal during transmission, introducing distortion in the video received at the ground. In some cases, the loss of signal is so severe; no information is received in portions of an image frame. To improve the corrupt video, we capitalize on the oversampling in the temporal domain (across video frames), applying a data fusion approach to de-noise the video. The resulting video retains the significant scene content and dynamics, without distracting artifacts from noise. This allows humans to easily ingest the information from the video, and make it possible to utilize further video exploitation algorithms such as object detection and tracking.

Citation Download Citation

Amber D. Fischer and Kyle J. Hildebrand "Temporal fusion for de-noising of RGB video received from small UAVs", Proc. SPIE 7668, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII, 76680V (26 April 2010); https://doi.org/10.1117/12.851810

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