Image interpolation estimates the gray values of unknown pixels based on known ones. It is a process of data generation. The objective is to increase the resolution of an image through upsampling. Firstly,the difference between image interpolation and image super-resolution reconstruction is analyzed. Then, the developments of various algorithms on image interpolation are reviewed and their features are analyzed. In particular, ′what is an edge′ is explained for edge-guided interpolation techniques. Furthermore, some subjective and objective image quality assessments are introduced. Meanwhile, the effects of image interpolation with different downsmapling methods are illustrated experimentally. Finally, the future research direction in the field is given.