Game theory based band selection for hyperspectral images

This paper proposes a new evaluation criterion for band selection for hyperspectral imagery. The combination of information and class separability is used to be as a new evaluation criterion, at the same time, the correlation between bands is used as a constraint condition. In addition, the game theory is introduced into the band selection to coordinate the potential conflict of search the optimal band combination using information and class separability these two evaluation criteria. The experimental results show that the proposed method is effective on AVIRIS hyperspectral data.