Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)

Classification Precision Analysis on Different Fusion Algorithm for ETM + Remote Sensing Image

Authors
Huoqian Luo
Corresponding Author
Huoqian Luo
Available Online September 2016.
DOI
10.2991/icence-16.2016.184How to use a DOI?
Keywords
Fusion algorithm, ETM +, Remote sensing image fusion, The classification accuracy
Abstract

With ETM+ data (Nantai Island Fuzhou), several fusion algorithms (PCA, MLT, Brovey Transform, HIS) have been applied in image fusion. After image fusion, some criterions (Spectral fidelity, High spatial frequency information gain, and Classification accuracy, Etc.) have been utilized to evaluate the effect of fusion. Based on the fusion image, unsupervised classification and sequential accuracy assessment have been applied to it. According to the experiment result mentioned above, the paper provides a methodology reference of image fusion to user.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-229-9
ISSN
2352-538X
DOI
10.2991/icence-16.2016.184How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Huoqian Luo
PY  - 2016/09
DA  - 2016/09
TI  - Classification Precision Analysis on Different Fusion Algorithm for ETM + Remote Sensing Image
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 983
EP  - 990
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.184
DO  - 10.2991/icence-16.2016.184
ID  - Luo2016/09
ER  -