Scale-Aware Multispectral Fusion of RGB and NIR Images Based on Alternating Guidance

Abstract

In low light condition, color (RGB) images captured by increasing the camera ISO contain much noise and detail loss. However, near infrared (NIR) images are robust to noise and have clear textures without color. In this paper, we propose scale-aware multispectral fusion of RGB and NIR images based on alternating guidance. Low light RGB images provide large-scale image structure and color information, while NIR images have fine details lost in RGB images. Since they are complementary, we adopt alternating guidance for the fusion of them using weighted least squares (WLS). First, we perform the first guidance to denoise the RGB image and obtain base layer. Then, we conduct the second guidance for scale-aware detail transfer of the NIR image and yield detail layer. Finally, we combine the base and detail layers to generate a fusion image. We maximize the multispectral advantage of RGB and NIR images for fusion based on alternating guidance. Experimental results show that the proposed method achieves good performance in noise reduction, detail transfer and color reproduction, and is superior to the state-of-the-art ones in terms of quantitative measurement and computational efficiency.

Keywords

• Image fusion
• alternating guidance
• detail transfer
• weighted least squares
• scale-aware