The retrieval of images in remote sensing databases is based on world-oriented information like the location of the scene, the utilised scanner, and the date of acquisition. However, these descriptions are not meaningful for many users who have a limited knowledge about remote sensing but nevertheless have to work with satellite imagery. Therefore a content-based dynamic retrieval technique using a cluster architecture to fulfil the resulting computational requirements is proposed. Initially the satellite images are distributed evenly over the available computing nodes and the retrieval operations are performed simultaneously. The dynamic strategy creates the need for a workload balancing before the sub-results are joined in a final ranking.
CITATION STYLE
Bretschneider, T., & Kao, O. (2002). Retrieval of multispectral satellite imagery on cluster architectures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2400, pp. 342–345). Springer Verlag. https://doi.org/10.1007/3-540-45706-2_45
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