This letter proposes a double-attentive principle component analysis (DA-PCA) model for image processing. Compared to the previous PCA-based works that cannot deal with normal images and outliers effectively, the proposed DA-PCA model performs a double-attentive mechanism to sever the connections with outliers and hold the effectiveness of normal images. To solve the proposed DA-PCA model, we propose an efficiently iterative algorithm and provide strict convergence analysis for it. Moreover, in the simulations, we conduct the reconstruction and classification experiments on several real datasets and the experimental results demonstrate the superb performance of our proposal.

中文翻译：

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双注意力主成分分析

这封信提出了一种用于图像处理的双注意主成分分析 (DA-PCA) 模型。与之前无法有效处理正常图像和异常值的基于 PCA 的工作相比，所提出的 DA-PCA 模型执行双重注意机制来切断与异常值的连接并保持正常图像的有效性。为了解决提出的 DA-PCA 模型，我们提出了一种高效的迭代算法并为其提供严格的收敛分析。此外，在模拟中，我们对几个真实数据集进行了重建和分类实验，实验结果证明了我们的建议的卓越性能。