An efficient eigen-space approach for management of satellite image databases

In this study, we propose an efficient approach, which consists of an algorithm to speed up the multi-dimensional image segmentation and an efficient automatic mechanism to manage satellite image databases. Concerning image segmentation, we develop a 1D segmentation technique by an eigen-subspace projection approach, which can perform the image segmentation efficiently by transforming the multi-dimensional image data into 1D projection length. In addition, we develop a data model of the eigen-index by a probabilistic approach. Based on the maximum a posterior probability (MAP) information criterion, the management scheme may determine the accuracy of the user added data entry. Therefore, the DB archive can be managed efficiently. Simulation results performed on SPOT images have demonstrated the proposed approach is suitable for management of satellite image databases

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