A nonlinear mean square estimation algorithm for cross-sensor image fusion and spectral anomaly detection is described. The algorithm can be used to enhance a low resolution image with a higher resolution coregistered multispectral image, and to detect anomalies between spectral bands (features in one spectral band that do not occur in other bands). Experimental results for Landsat data are presented illustrating the spatial enhancement of thermal imagery, the detection of thermal anomalies (heat sources), and the detection of smoke plumes.
Mark J. Carlotto, Mark J. Carlotto,
"Cross-sensor image fusion and spectral anomaly detection", Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); doi: 10.1117/12.477626; https://doi.org/10.1117/12.477626