# Infrared and Visible Image Fusion: Methods, Datasets, Applications, and Prospects
## 1 Introduction  
Image fusion tries to create an image rich in numerous aspects and information using a variety of techniques as an enhancement strategy. Combining the images produced by several sensors is the process of image fusion. The continuous advancement of current science and technology has led to the development of picture fusion technology since images with a single piece of information are unable to satisfy people's needs [1]. Infrared and visible image fusion [2], multi-focus image fusion, medical image fusion, remote sensing image fusion, etc. are the main divisions of image fusion. Infrared and visible picture fusion is the more commonly utilized technology among the four types of image fusion mentioned above. The visible light band, which has great resolution and an exceptionally detailed texture, is the most consistent with the visual field of human eyes and produces images that are quite similar to those seen in people's daily lives. However, it will be significantly disrupted by shielding, the weather, and other things. The ability to recognize and identify targets in infrared images allows for thecapture of thermal targets even in the most challenging weather situations, such as heavy rain or smoke. On the other hand, low resolution, fuzziness, and poor contrast are further drawbacks of infrared images. In order to improve the visual sensory level of the image, we can combine the advantages of the two when we use a specific fusion method, resulting in a fused image that not only has clear infrared targets in the infrared image but also has more abundant texture details in the visible image [3]. In practical applications, the merging of infrared and visible images can address a variety of issues. For instance, in some situations, the operator must simultaneously monitor a large number of visible and infrared images from the same scene, each of which has its own unique set of requirements. Humans find it very challenging to combine information from visible and infrared images simply by gazing at a variety of them. In some situations with complicated backdrops, infrared images can overcome the constraints of visible images and acquire target information at night or in low-illumination settings, improving the capability of target identification and recognition. The effectiveness of the work process can be substantially increased and convenience is brought about by fusing infrared and visible photographs. At the same time, a wide range of applications for infrared and visible image fusion exist in the fields of night vision, biometric recognition, detection, and tracking [4]. This highlights the importance of infrared and visible image fusion studies. Image fusion technology was initially proposed in the 1980s, according to literary sources. The use of the Laplacian pyramid approach in binocular picture fusion was first suggested by [PERSON] et al [5]. Later, [PERSON] et al. [6] created a fusion technique that builds images with increased depth of field using the Laplacian methodology. [PERSON] et al. 's [7] monitoring of infrared and visible image fusion [8] employed a variety of pyramid techniques. [PERSON] et al. 's [9] proposal to use the discrete wavelet transform in the area of picture fusion was made in the 1990s. A binary wavelet transform that is orientable was proposed by [PERSON] et al [10]. In order to fuse visible and infrared images, [PERSON] [11] et al. devised an image fusion technique based on a biological model of color vision [12]. Academician [PERSON] used three-dimensional reconstruction to apply fusion images gathered from various perspectives [13]. A real-time picture fusion demonstration system was developed in the UK in 2002, and it can help pilots find hidden targets on the ground and enhance their visual sensory capacity when helicopters fly at low altitudes [14]. A brand-new technique for photovoltaic array problem diagnostics based on infrared and visible image fusion technology was put out by [PERSON] et al. in 2003 [15].