Multi-view face hallucination using SVD and a mapping model

Multi-view face hallucination (MFH) presents a challenge issue in face recognition domain. In this paper, an efficient method based on singular value decomposition (SVD) and a mapping model is proposed for multi-view face hallucination. Based on an approximately same linear mapping relationship across different views, two corresponding matrices obtained from the SVD of the low resolution (LR) image for the high-resolution (HR) multi-view face images can be constructed via the mapping model using global reconstruction. Experiments show that our proposed multi-view face-hallucination scheme is effective and produces promising super-resolved results. (C) 2019 Elsevier Inc. All rights reserved.