Abstract
In this paper, we propose a new learning-based super-resolution method, which utilizes the Principal Components Analysis(PCA) to remove noise, which includes in the learning-based process when its database redundancy is removed. The proposed algorithm significantly reduces the complexity and maintains a comparable image quality.
