Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy

Szu-Chi Chung, Shao-Hsuan Wang, Po-Yao Niu +3

Principal component analysis (PCA) is arguably the most widely used dimension-reduction method for vector-type data. When applied to a sample of images, PCA requires vectorization…