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Using physics-based invariant representations for the recognition of regions in multispectral satellite images

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2 Author(s)
G. Healey ; Comput. Vision Lab., California Univ., Irvine, CA, USA ; A. Jain

We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. The representations and algorithms are derived for this application from a physical model for the formation of multispectral satellite images. The use of several representations and algorithms is necessary to interpret the diversity of physical and geometric structure in these images. Algorithms are used that exploit multispectral distributions, multispectral spatial structure, and labeled classes. The performance of the system is demonstrated on a large set of multispectral satellite images taken over different areas of the United States under different illumination and atmospheric conditions

Published in:

Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on

Date of Conference:

18-20 Jun 1996