Cross-sensor image fusion and spectral anomaly detection | Zendy

Mark J. Carlotto | Zendy

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<title>Cross-sensor image fusion and spectral anomaly detection</title>

Author(s) -

Mark J. Carlotto

Publication year - 2002

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.477626

Subject(s) - multispectral image , anomaly (physics) , image fusion , image resolution , anomaly detection , spectral bands , image (mathematics) , remote sensing , fusion , spectral resolution , resolution (logic) , sensor fusion , artificial intelligence , computer science , computer vision , pattern recognition (psychology) , physics , geology , spectral line , linguistics , philosophy , condensed matter physics , astronomy

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.

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