Spectrum Characteristics Preserved Visible and Near-Infrared Image Fusion Algorithm

Abstract

The visible and near-infrared images fusion aims at utilizing their spectrum characteristics to enhance visibility. However, the current visible and near-infrared fusion algorithms cannot well preserve spectrum characteristics, which results in color distortion and halo artifacts. Therefore, this paper proposes a new visible and near infrared images fusion algorithm by fully considering their different reflection and scattering characteristics. According to image degradation model, the reflection weight model and the transmission weight model are established, respectively. The reflection weight model is established by calculating the difference between the visible (red, green, and blue) spectra and the near-infrared spectrum, while maintaining the correlation of the visible spectra. The proposed reflection weight model can preserve the original reflection characteristic of objects in natural scenes. On the other hand, the transmission weight model is explicitly proposed by calculating the gradient ratio of the visible spectra to the near-infrared spectrum. The proposed transmission weight model intends to make full use of the strong transmission performance of the near-infrared spectrum, which can complement the details loss of the visible spectra caused by light scattering. Moreover, the fused image based on two models is further enhanced according to the reflection characteristics of near-infrared spectrum in case of the non-uniform illumination. The experimental results demonstrate that the proposed algorithm can not only well preserve spectrum characteristics, but also avoid color distortion while maintaining the naturalness, which outperforms the state-of-the-art.