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In this paper, a patch-based super-resolution (SR) method is proposed to hallucinate facial images. Two steps are involved in this method. In the first step, semi-kernel partial least squares (semi-KPLS) algorithm is used to generate a nonlinear correlative space. In the second step, we use collaborative representation (CR) to infer a high-resolution (HR) face. The experiments conducted on FERET database demonstrate the proposed algorithm can generate better results, in comparison with some state-of-the-art approaches.

Face Hallucination via Semi-Kernel Partial Least Squares