An approach to feature selection and classification of remote sensing images based on the Bayes rule for minimum cost
- 1 January 2000
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Geoscience and Remote Sensing
- Vol. 38 (1) , 429-438
- https://doi.org/10.1109/36.823938
Abstract
No abstract availableThis publication has 22 references indexed in Scilit:
- Classification of Mediterranean vegetation by TM and ancillary data for the evaluation of fire riskInternational Journal of Remote Sensing, 2000
- Quality assessment of image classification algorithms for land-cover mapping: A review and a proposal for a cost-based approachInternational Journal of Remote Sensing, 1999
- Mixed pixel classification with robust statisticsIEEE Transactions on Geoscience and Remote Sensing, 1997
- Feature selection: evaluation, application, and small sample performancePublished by Institute of Electrical and Electronics Engineers (IEEE) ,1997
- A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classificationIEEE Transactions on Geoscience and Remote Sensing, 1995
- Texture classification in aerial photographs and satellite dataInternational Journal of Remote Sensing, 1992
- Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing DataIEEE Transactions on Geoscience and Remote Sensing, 1990
- Review Article A review of multi-channel indices of class separabilityInternational Journal of Remote Sensing, 1987
- A Branch and Bound Algorithm for Feature Subset SelectionIEEE Transactions on Computers, 1977
- Textural Features for Image ClassificationIEEE Transactions on Systems, Man, and Cybernetics, 1973