Color Face Hallucination Using Neighbor Locality Representation and Inter-Channel Correlation

Recently, the locality-constrained linear coding (LLC) based techniques have been widely exploited for face hallucination. However, for the color face image, the conventional LLC model ignores the neighbor self-similarity prior as well as the relevance of different color channels, resulting in unsatisfactory representations. This paper presents a novel Neighbor locality Representation and inter-Channel Correlation (NRCC) model for color face hallucination. Compared with conventional LLC, NRCC makes full use of neighbor self-similarity prior and takes advantage of the co-manifold structure among RGB channels. The neighbor self-similarity prior and co-manifold structure can make the reconstruction results of eyes and lips generated from the proposed method better than those from other methods. The experimental results in some public face databases indicated the superiority of the proposed method over the prior art face hallucination methods.