Sub-pixel mapping based on memetic algorithm for hyperspectral imagery

In this paper, sub-pixel mapping based on memetic algorithm (SMMA) is proposed to perform the sub-pixel mapping task, including a global search and a local search. In the global search, a clonal selection algorithm can be used,. To increase the convergence speed, the local search is designed to search for a feasible solution in the neighborhood of the candidate sub-pixel mapping solutions. In addition, a new post-processing method is designed to decrease the effect of the spectral unmixing errors. The experimental results demonstrate that SMMA is superior to the traditional methods.