Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters

Abstract

In this study, a crater detection system for a large-scale image database is proposed. The original images are grouped according to spatial frequency patterns and both optimized parameter sets and noise reduction techniques used to identify candidate craters. False candidates are excluded using a self-organizing map (SOM) approach. The results show that… (More)
DOI: 10.1007/3-540-45884-0_29

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Cite this paper

@inproceedings{Honda2002MiningOT, title={Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters}, author={Rie Honda and Yuichi Iijima and Osamu Konishi}, booktitle={Progress in Discovery Science}, year={2002} }