A super-resolution based method to synthesize visual images from near infrared

In this paper, we propose a new method to enhance the quality of near infrared face image using tensorface, super-resolution and image fusion. Given a single model of near infrared face image which is not suitable for human to recognize or verify and its low-resolution sample, we can synthesize an image under visible light environment by building multiple factors training tensors and super-resolving its high-resolution visible light reconstructions across different modalities. The training tensor space consists of near infrared and visible light face images pairs of different people. Fusion is performed between the reconstructions and the original near infrared images. Experiments show promising results of synthesized visible light face images.