Abstract
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.
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Zhuo, H., Lam, KM. (2010). Wavelet-Based Eigentransformation for Face Super-Resolution. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15696-0_21
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DOI: https://doi.org/10.1007/978-3-642-15696-0_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15695-3
Online ISBN: 978-3-642-15696-0
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