Deep Fusion of RGB and NIR Paired Images Using Convolutional Neural Networks

In low light condition, the captured color (RGB) images are highly degraded by noise with severe texture loss. In this paper, we propose deep fusion of RGB and NIR paired images in low light condition using convolutional neural networks (CNNs). The proposed deep fusion network consists of three independent sub-networks: DenoisingNet, EnhancingNet, and FusionNet. We build a denoising sub-network to eliminate noise from noisy RGB images. After denoising, we perform an enhancing sub-network to increase the brightness of low light RGB images. Since NIR image contains fine details, we fuse it with the Y channel of RGB image through a fusion subnetwork. Experimental results demonstrate that the proposed method successfully fuses RGB and NIR images, and generates high quality fusion results containing textures and colors.