Pixel level fusion of multispectral face images: Short review

Abstract

With the recent rapid development in the field of multispectral face imaging, the use of image fusion has emerged as a new and important research area. Many studies have attempted to improve the performance of face recognition by fusing the infrared (IR) and visible face images, yet few comparison studies have been conducted to examine which fusion method is preferable over another. In this paper, we provide an overview of the most widely used pixel level fusion algorithms, and establish a comparison to evaluate each fusion method Our experiments were validated by comparing cumulative match characteristics (CMC) of multispectral image fusion by weighted sum, principal component analysis, empirical mode decomposition, and wavelet transform.