A modified algorithm for multi-target detection in hyperspectral image

In the area of hyperspectral image detection, Constrained Energy Minimization (CEM) algorithm has received considerable interest recently. However, it is very sensitive to noise and can only detect one target at one time. In order to solve this problem, Winner-Take-All Constrained Energy Minimization (WTACEM) was proposed. Based on it, we propose a modified multi-target detection approach. We study the sample correlation matrix and find if we exclude the desired target pixel vectors from the correlation matrix, we can achieve better results. The simulation results indicate that the errors caused by the modified WTACEM have decreased obviously and the output is more close to the true abundance fraction. The experiment also shows that when the abundance fraction of target increases, the detection performance improves.