Title of article :
Early fire detection using non-linear multitemporal prediction of thermal imagery
Author/Authors :
Koltunov، نويسنده , , Carlos A. and Ustin، نويسنده , , S.L.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
11
From page :
18
To page :
28
Abstract :
This paper presents a sub-pixel thermal anomaly detection method based on predicting background pixel intensities using a non-linear function of a plurality of past images of the inspected scene. At present, the multitemporal approach to thermal anomaly detection is in its early development stage. In case of space-borne surveillance the multitemporal detection is complicated by both spatial and temporal variability of background surface properties, weather influences, viewing geometries, sensor noise, residual misregistration, and other factors. We use the problem of fire detection and the MODIS data to demonstrate that advanced multitemporal detection methods can potentially outperform the operationally used optimized contextual algorithms both under morning and evening conditions.
Keywords :
Fire detection , anomaly detection , Target Detection , Change detection , Dynamic Detection Model , multitemporal , thermal infrared , MODIS , Surveillance
Journal title :
Remote Sensing of Environment
Serial Year :
2007
Journal title :
Remote Sensing of Environment
Record number :
1575180
Link To Document :
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