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Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations
August 1996 (vol. 18 no. 8)
pp. 842-848

Abstract—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.

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Index Terms:
Image database,image retrieval, color constancy, satellite images, color, machine vision, texture, computer vision, recognition.
Citation:
Glenn Healey, Amit Jain, "Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 842-848, Aug. 1996, doi:10.1109/34.531804
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