Low‐light image enhancement for infrared and visible image fusion

Abstract

Abstract Infrared and visible image fusion (IVIF) is an essential branch of image fusion, and enhancing the visible image of IVIF can significantly improve the fusion performance. However, many existing low‐light enhancement methods are unsuitable for the visible image enhancement of IVIF. In order to solve this problem, this paper proposes a new visible image enhancement method for IVIF. Firstly, the colour balance and contrast enhancement‐based self‐calibrated illumination estimation (CCSCE) is proposed to improve the input image's brightness, contrast, and colour information. Then, the method based on Mutually Guided Image Filtering (muGIF) is adopted to design a strategy to extract details adaptively from the original visible image, which can keep details without introducing additional noise effectively. Finally, the proposed visible image enhancement technique is used for IVIF tasks. In addition, the proposed method can be used for the visible image enhancement of IVIF and other low‐light images. Experiment results on different public datasets and IVIF demonstrate the authors’ method's superiority from both qualitative and quantitative comparisons. The authors’ code will be publicly available at https://github.com/yiqiao666/low‐light‐enhancement‐for‐IVIF/tree/master.

Keywords

• image denoising
• image enhancement
• image fusion