Edge-directed interpolation based on shifted-linear image model

This paper presents a hybrid image interpolation algorithm to keep details and edges simultaneously. The basic idea is to separate the unknown pixels into two classes and estimate them in different way. One class of unknown pixels is obtained via shifted linear interpolation and the other class through statistical signal processing method. The merit of this hybrid algorithm is that each unknown pixel can be estimated through original pixels simultaneously. Simulation results demonstrate that this hybrid interpolation algorithm improves the quality of the interpolated images over conventional interpolation methods.