Wavelet-Based Eigentransformation for Face Super-Resolution.

In this paper, we propose a new approach to human face hallucination based on eigentransformation. In our algorithm, a face image is decomposed into different frequency bands using wavelet transform, so that different approaches can be applied to the low-frequency and high-frequency contents for increasing the resolution. The interpolated LR images are decomposed by the forward wavelet transform, whereby the low-frequency content is simply interpolated, while the wavelet coefficients of the three high-frequency bands are used to estimate the corresponding ones of the HR image by using eigentransformation. The approximation coefficients are reconstructed directly based on the content of the interpolated LR image. The reconstructed image can be synthesized by the inverse wavelet transform with all the estimated coefficients. [ABSTRACT FROM AUTHOR]