Infrared image super-resolution using auxiliary convolutional neural network and visible image under low-light conditions

Convolutional neural networks (CNN) have been successfully applied to visible image super-resolution (SR) methods. In this study, we propose a CNN-based SR algorithm for up-scaling near-infrared (NIR) images under low-light conditions, using corresponding visible images. Our algorithm first extracts high-frequency (HF) components from the up-scaled low-resolution (LR) NIR image and its corresponding high-resolution (HR) visible image, and then...