Noise Robust Face Hallucination via Locality-Constrained Representation

摘要: Recently, position-patch based approaches have been proposed to replace the probabilistic graph-based or manifold learning-based models for face hallucination. In order to obtain the optimal weights of face hallucination, these approaches represent one image patch through other patches at the same position of training faces by employing least square estimation or sparse coding. However, they cannot provide unbiased approximations or satisfy rational priors, thus the obtained representation is not satisfactory. In this paper, we propose a …