The similarity of one image plays an important role in super-resolution reconstruction. However

a single image can not provide sufficient similarity information. Therefore

a video super-resolution reconstruction algorithm based on similarity constraints is proposed. Making initial motion estimation with flow field and fine block matching

the similar information

which can be used to modify the reconstruction error in iterative process of iterative back projection

will be extracted from video sequences. The experimental results show that the proposed algorithm has improve a the image details

moreover

it can remove the artifacts and obtain clear and sharp edges in visual perception.