NDLI: A stepwise refinement classification method of remote sensing image based on feedback strategies

Content Provider	IEEE Xplore Digital Library
Author	Xianchuan Yu Shanshan Bian Xin Zhou Guian Wang Hui He Weijie An
Copyright Year	2014
Description	Author affiliation: Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing, China (Xianchuan Yu; Shanshan Bian; Xin Zhou; Hui He; Weijie An) \|\| Libr., Beijing Normal Univ., Beijing, China (Guian Wang)
Abstract	This paper focus on two phenomena that "same spectrum with different objects" and "same object with different spectra" in multispectral remote sensing image, and propose a stepwise refinement classification method based on multi-sensitive strategies. It's a top-down, gradually refinement hierarchical way of classification which combines with advantages of both supervised classification and unsupervised classification: by analyzing the characteristic of spectrum curve, cluster and find out the band combinations with big characteristic differences as the guidance of classification; according to spectral characteristics of different bands combinations, choose different methods for further fine classification. Experimental results show that the proposed method achieved the high accurate classification of multispectral remote sensing images and effectively overcome the both above phenomena. Furthermore, the overall accuracy and kappa coefficient also confirm its superior performance.
Sponsorship	IEEE Geosci. Remote Sens. Soc.
Starting Page	1694
Ending Page	1697
File Size	826158
Page Count	4
File Format	PDF
ISBN	9781479957750
DOI	10.1109/IGARSS.2014.6946776
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-13
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Remote sensing Image classification Artificial neural networks Soil Educational institutions Principal component analysis Feedback Strategies Image Classification Stepwise Refinement
Content Type	Text
Resource Type	Article

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