The Color Face Hallucination with the Linear Regression Model and MPCA in HSV Space

This paper proposes a novel hallucination technique, color face images reconstruction of HSV space with a regression model in multilinear principal component analysis (MPCA). From hallucination framework, many color face images are explained in HSV space. Then, they can be naturally described as tensors or multilinear arrays. This novel hallucination technique can perform feature extraction by determining a multilinear projection that captures most of the original tensorial input variation. In this contribution we show that our hallucination technique can be suitable for color face images both in HSV space. By using the tensor MPCA subspace with regression model, we can generate photorealistic color face images. Our approach is demonstrated by extensive experiments with highquality hallucinated color faces. In addition, our experiments on face images from FERET database validate our algorithm.