Many image interpolation algorithms have been developed in the recent past aiming for high prediction accuracy. But these algorithms are focused only towards better predictor design. In this paper, we propose a generic two phase image interpolation algorithm based upon error feedback mechanism. In the first phase, we learn error pattern occurred during interpolation of down sampled version of original Low Resolution (LR) image. It is assumed that similar error pattern also occurrs during the interpolation of original LR image. Hence, error pattern learnt in first phase, is employed during the interpolation of original LR image (second phase). From extensive experiments, we found that our algorithm gives a significant improvement in prediction accuracy of existing interpolation algorithms. In particular, our algorithm plays a significant role in improving prediction accuracy of those algorithms which have inherently poor prediction capability for certain types of images. © 2013 IEEE.