Accurate sub-pixel image registration is a key problem in image super-resolution reconstruction.Optical flow methods based on pixel feature

which are widely used in image super-resolution reconstruction

are difficult to achieve registration of sub-pixel accuracy for large motion field.This paper considered a robust multi-frame image super-resolution reconstruction method based on SIFT.Firstly

SIFT operator was used to pick up keypoints and their descriptors of input low-resolution image pairs which are to be registered.Then the candidate keypoint pair was selected

outliers were wiped off through RANSAC

and images pair displacement was computed at the basis of assumed transitional geometry constraint model.Secondly

initial reference frame was selected from vision center frame or specified image frame.Lastly

super-resolution reconstruction was done through conventional super-resolution reconstruction framework.Experimental results show that the proposed image super-resolution reconstruction method based on SIFT is feasible

and the quality of super-resolution reconstructed images is better than those of classical methods by both subjective evaluation and objective standards.