中文摘要：

稀疏表示方法已经被成功应用于高光谱图像目标检测领域,并且取得了较好的检测效果,但由于高光谱图像往往具有很大的数据量,传统的稀疏检测算法计算成本很高。针对这种情况,提出了应用St OMP算法的高光谱图像稀疏目标检测算法,对求解稀疏系数的步骤进行了改进,减少了此过程中的迭代次数,大幅度降低了运算量,提高了检测速度。使用了2组数据进行仿真实验,结果表明,St OMP算法的应用有效地提高了检测速度与检测精度。

英文摘要：

This paper proposes a new hyperspectral image（ HSI） target detection method using St OMP reconstruction algorithm. St OMP could be used for the case when the computing cost of traditional sparse detection algorithms is very high because the HSI often has a large amount of data. The sparse representation algorithm has been successfully applied to the field of HSI target detection and it has achieved good results. The new method improves the step of solving sparse coefficients,reducing the number of iterations of this process,which significantly improves the detection efficiency and reduces the computing cost. There are two sets of data in the simulation experiment and the results showed that the St OMP algorithm improves the detection speed and precision effectively.