查看文章

A swarm intelligence theory has been widely applied for the endmember extraction due to its mathematical tractability and its improved performance without prior information. We proposed an endmember extraction algorithm using particle swarm optimization (EEA-PSO). It is equipped with an advantage of the adaptive tuning parameter free mechanism. The particle swarm optimization is used to search the optimal endmember combination in the feasible solution space, where the movement of each particle has been influenced by its local and global best positions. The proposed method has advantages such as high efficiency, rapid convergence, and a strong capability of global search. In addition, the proposed approach is also equipped with an advantage of the simplex geometry by initializing one of the initial random population using minimum volume simplex analysis algorithm (MVSA). The adaptive strategy …