The necessity of image fusion is growing in recently in image processing applications due to the tremendous amount of acquisition systems. Fusion of images is defined as an alignment of noteworthy Information from diverse sensors using various mathematical models to generate a single compound image. The fusion of images is used for integrating the complementary multi-temporal, multi-view and multi-sensor Information into a single image with improved image quality and by keeping the integrity of important features. It is considered as a vital pre-processing phase for several applications such as robot vision, aerial, satellite imaging, medical imaging, and a robot or vehicle guidance. In this paper, various state-of-art image fusion methods of diverse levels with their pros and cons, various spatial and transform based method with quality metrics and their applications in different domains have been discussed. Finally, this review has concluded various future directions for different applications of image fusion.

由于大量的采集系统，最近在图像处理应用中图像融合的必要性越来越大。图像融合被定义为使用各种数学模型将来自不同传感器的值得注意的信息对齐以生成单个复合图像。图像融合用于将互补的多时间、多视图和多传感器信息集成到单个图像中，提高图像质量并保持重要特征的完整性。它被认为是机器人视觉、航空、卫星成像、医学成像以及机器人或车辆引导等多种应用的重要预处理阶段。在本文中，各种不同级别的最新图像融合方法及其优缺点，讨论了具有质量度量的各种基于空间和变换的方法及其在不同领域的应用。最后，本综述总结了图像融合不同应用的各种未来方向。