Abstract: The parallel algorithms design and implementation of covariance matrix, related to PCA and MNF, and SCM used in hyperspectral remote sensing image data process was discussed in this paper. The covariance matrix parallel algorithm was designed and implemented under cluster circumstance based on MPI. On the other hand, parallel algorithm of SCM was designed and implemented based on GPU. Both of these two parallel algorithms were verified during the application on hyperspectral remote sensing data processing. The experiment results prove that high performance computing is effective during the data process of hyperspectral remote sensing image, and it should be an important technique for generalization of hyperspectral remote sensing to engineering quick application. The results also prove the correctness of the parallel algorithms proposed in this paper.