Analysis of Image Fusion Techniques based on Quality Assessment Metrics

Objective: The objective of Image Fusion is to combine the relevant and essential information from several images into a single image, which is highly informative than any of the source images such that the resultant fused image will be more appropriate for human visual perception and for image processing tasks like segmentation, feature extraction and object recognition. Methods: This paper presents the basic concepts, various types and levels of fusion, literature review of non-transform and transform based image fusion techniques from the perspective of their applications, advantages and limitations. Findings: The performance of existing image fusion methods along with various assessment metrics that determine the quality of fused images are evaluated and theoretically analyzed. It is found that the computational complexity is considerably reduced in Discrete Cosine Transformation based methods. Applications: Image Fusion has been effectively applied to many fields such as Remote Sensing, Military affairs, Machine Vision, Medical imaging, and so on.