Proceedings of the 2016 International Conference on Engineering and Technology Innovations

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A Polymorphic Ant Colony Algorithm (PACA) for the Selection of Optimized Band Selection of Hyperspectral Remote Sensing Image

Authors
Xiaohui Ding, Shuqing Zhang, Huapeng Li
Corresponding Author
Xiaohui Ding
Available Online March 2016.
DOI
10.2991/iceti-16.2016.37How to use a DOI?
Keywords
Hyperspectral, Dimensionality Reduction, Band Selection, Ant Colony Algorithm, Polymorphic Ant Colony Algorithm
Abstract

With the definite labeled samples, it is difficult that avoid the curse of the dimensionality for the accurate and efficient classification of hyperspectral images. It is necessary that reduce the dimensionality of hyperspectral images. Therefore, Polymorphic Ant Colony Algorithm (PACA) based band selection algorithm (PACA-BS) for hyperspectral images is proposed in this paper. Compared with the common Ant Colony Algorithm (ACA) based band selection algorithm (ACA-BS), PACA-BS can significantly decrease the searching space and thus the time complexity. These algorithms are applied to select the bands of Hyperion and AVIRIS hyperspectral image according to the class separability criterion. Performance evaluation of algorithms is focused on the following aspects: computing time and overall classification accuracy. The results showed that the computing time of PACA-BS was markedly lower than ACA-BS. Furthermore, band sets of PACA-BS generate a higher overall classification accuracy. The PACA-BS is thus proved to be a promising and optimized method for band selection of hyperspectral image.

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 2016 International Conference on Engineering and Technology Innovations
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/iceti-16.2016.37
ISSN
2352-5401
DOI
10.2991/iceti-16.2016.37How 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

risenwbib
TY  - CONF
AU  - Xiaohui Ding
AU  - Shuqing Zhang
AU  - Huapeng Li
PY  - 2016/03
DA  - 2016/03
TI  - A Polymorphic Ant Colony Algorithm (PACA) for the Selection of Optimized Band Selection of Hyperspectral Remote Sensing Image
BT  - Proceedings of the 2016 International Conference on Engineering and Technology Innovations
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceti-16.2016.37
DO  - 10.2991/iceti-16.2016.37
ID  - Ding2016/03
ER  -