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Authors: Dragos Bratasanu 1 ; Ion Nedelcu 1 and Mihai Datcu 2

Affiliations: 1 Romanian Space Agency ROSA, Romania ; 2 DLR German Aerospace Center, Germany

ISBN: 978-989-8425-33-1

Keyword(s): .

Abstract: The Earth Observation processing tools operating in the recent scenario need to be tailored to the new products offered by the sub-meter spatial resolution imaging sensors. The new methods should provide the image analysts the essential automatic support to discover relevant information and identify significant elements in the image. We advocate an automatic technique to select the optimum number features used in classification, object detection and analysis of optical satellite images. Using measures of mutual information between the target classes and the available features, we investigate the criterions of maximum-relevance and maximum-relevance-minimumredundancy for automatic feature selection at very-low cost. Following a comprehensive set of experiments on multiple sensors, applications and classifiers, the results demonstrate the possible operational use of the method in future scenarios of human-machine interactions in support of Earth Observation technologies.

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Paper citation in several formats:
Bratasanu, D.; Nedelcu, I. and Datcu, M. (2010). Automatic Feature Selection for Operational Scenarios of Satellite Image Understanding using Measures of Mutual Information.In Proceedings of the International Workshop on Semantic Sensor Web - Volume 1: SSW, (IC3K 2010) ISBN 978-989-8425-33-1, pages 109-117. DOI: 10.5220/0003143101090117

@conference{ssw10,
author={Dragos Bratasanu. and Ion Nedelcu. and Mihai Datcu.},
title={Automatic Feature Selection for Operational Scenarios of Satellite Image Understanding using Measures of Mutual Information},
booktitle={Proceedings of the International Workshop on Semantic Sensor Web - Volume 1: SSW, (IC3K 2010)},
year={2010},
pages={109-117},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003143101090117},
isbn={978-989-8425-33-1},
}

TY - CONF

JO - Proceedings of the International Workshop on Semantic Sensor Web - Volume 1: SSW, (IC3K 2010)
TI - Automatic Feature Selection for Operational Scenarios of Satellite Image Understanding using Measures of Mutual Information
SN - 978-989-8425-33-1
AU - Bratasanu, D.
AU - Nedelcu, I.
AU - Datcu, M.
PY - 2010
SP - 109
EP - 117
DO - 10.5220/0003143101090117

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