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An Information Theory-Based Scheme for Efficient Classification of Remote Sensing Data.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; Oct2017, Vol. 55 Issue 10, p5864-5876, 13p
- Publication Year :
- 2017
-
Abstract
- Information theory has recently become an interesting topic in earth observation data management and analysis, since it can provide important information on hidden interactions and correlations among the considered data records. Although several methods have been proposed and implemented to efficiently extract a proper set of features and deliver accurate image investigation, classification, and segmentation, these architectures show drawbacks when the data sets are characterized by complex interactions among the samples. In this paper, a new approach based on information theory for automatic pattern recognition is introduced for accurate classification of remotely sensed data. Experimental results carried out on real data sets show the validity of the proposed approach. [ABSTRACT FROM PUBLISHER]
- Subjects :
- REMOTE sensing
PATTERN perception
INFORMATION theory
PARETO optimum
BIG data
Subjects
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 55
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 125755621
- Full Text :
- https://doi.org/10.1109/TGRS.2017.2716187