Satellite image analysis using neural networks |
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Authors: | Roger A. Sheldon |
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Affiliation: | Ford Aerospace, 7375 Executive Place, Suite 400, Seabrook, Maryland 20706, USA |
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Abstract: | The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, Satellite Image Analysis using Neural Networks (SIANN), that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four-step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed has been completed and applied to climatological data. |
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