Region-based eigentransformation for face image hallucination
In this paper, we propose a region-based eigentransformation method for human face hallucination. The algorithm first uses the snake method to locate the targeted regions with high-frequency features in an edge-smoothed face mask, and then employs the eigentransformation to reconstruct the corresponding high-resolution counterpart. The resulting high-resolution face can be obtained by combining all of the reconstructed regions. As the boundaries of the respective high-frequency regions are also smooth, so the merging process at the boundaries will not produce visual artifacts. In addition, by segmenting the facial features into different regions, the eigentransformation can achieve a better performance level in reconstructing the high-frequency information. Experiments show that our proposed algorithm outperforms the original eigentransformation for face hallucination.