Human Face Super-Resolution Method Based on Train-Database

In this paper,we propose a human face super-resolution method based on training.This method composes similarity constrains of human face both in global and local manner.The local structure of human face ensures the solution of super-resolution to be in the space characterized by human face local structure.And the local structure in different scales instruct the searching to the optimal solution,then project the reconstructed face by local structure to the eigenface space determined by given human face database.Experiments show that the results have very good accuracy and high visual quality.