Face Hallucination via Similarity Constraints

Abstract

In this letter, we present a new face hallucination method based on similarity constraints to produce a high-resolution (HR) face image from an input low-resolution (LR) face image. This method is modeled as a local linear filtering process by incorporating four constraint functions at patch level. The first two constraints focus on checking if the training images are similar to the input face image. The third is defined in the HR face image, which is to impose the smoothness constraint between neighboring hallucinated patches. The final constraint computes the spatial distance to reduce the effect of patches that are far from the hallucinating patch. Experimental evaluation on a number of face images demonstrates the good performance of the proposed method on the face hallucination task.