Artificial bee colony algorithm-based band selection for hyperspectral imagery

Abstract:

A hyperspectral image band selection algorithm based on artificial bee colony algorithm isproposed to reducespectralredundancy of hyperspectral remote sensing image and computational complexity.Firstly, accordingtothecorrelationcoefficientmatrices among bands some pretreatments have been taken too btain the band sub space with less relevance. Then, neighborhood search has been implemented on each sub-space by using artificial bee colony algorithm together with the weighted sum between JM distance and OIF as the fitness function.To obtain the optimal band combination,the search is updated until the algorithm is convergent. Finally, the proposed algorithmis used to compare with band selection methods based on ACO, PSO and APO. The experimental results show that the proposed algorithm can not only ensure a good convergence but also reduce the computational cost. Simultaneously, when the obtained bands combination is used for hyperspectral image classification, higher classification accuracy can be obtained.