Video super-resolution using motion compensation and classification-aided fusion

In this paper, we propose a super-resolution algorithm based on image fusion via pixel classification. Two high-resolution images are constructed, the first by means of motion compensation and the second by means of image interpolation. The AdaBoost classifier is then used in the fusion of these images, resulting in an high-resolution frame. Experimental results show that the proposed method outperforms well-known video resolution enhancement methods while maintaining moderate computational complexity.