<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper uses the combination of information and class separability as a new evaluation criterion for hyperspectral imagery. Moreover, the correlation between bands is used as a constraint condition. The differential evolution algorithm is adopted during the search of optimal band combination. In addition, the game theory is introduced into the band selection to coordinate the potential conflict of searching the optimal band combination using information and class separability these two evaluation criteria. The experimental results show that the proposed method is effective.</p>
</abstract>

This paper uses the combination of information and class separability as a new evaluation criterion for hyperspectral imagery. Moreover, the correlation between bands is used as a constraint condition. The differential evolution algorithm is adopted during the search of optimal band combination. In addition, the game theory is introduced into the band selection to coordinate the potential conflict of searching the optimal band combination using information and class separability these two evaluation criteria. The experimental results show that the proposed method is effective.

A Hyperspectral Band Selection Based on Game Theory and Differential Evolution Algorithm

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This paper uses the combination of information and class separability as a new evaluation criterion for hyperspectral imagery. Moreover, the correlation...

A Hyperspectral Band Selection Based on Game Theory and Differential Evolution Algorithm

Publicado en línea: 01 dic 2016

Páginas: 1971 - 1990

Recibido: 18 mar 2016

Aceptado: 19 oct 2016

DOI: https://doi.org/10.21307/ijssis-2017-948

Palabras clave
Remote Sensing, Hyperspectral imagery, band selection, game theory, differential evolution algorithm

© 2016 Aiye Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A Hyperspectral Band Selection Based on Game Theory and Differential Evolution Algorithm

Publicado en línea: 01 dic 2016

Páginas: 1971 - 1990

Recibido: 18 mar 2016

Aceptado: 19 oct 2016

DOI: https://doi.org/10.21307/ijssis-2017-948

Palabras claveRemote Sensing, Hyperspectral imagery, band selection, game theory, differential evolution algorithm

© 2016 Aiye Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
Remote Sensing, Hyperspectral imagery, band selection, game theory, differential evolution algorithm