Abstract:
Image fusion has emerged as a major area of research in the past few decades due to its extended applications.
While progressing in the field of image fusion, a large number of techniques-based image transforms and spatial filters have
been devised for both general and specific sets of images. The primary criterion of image fusion technique is to deliver highquality visual perception besides giving a considerable objective evaluation rate. In this study, an information fusion rate-based
study is done on recent, most researched, and high-performing state-of-the-art techniques using visible and infrared image
datasets. These techniques have been chosen carefully, owing to their superiority in performance on both objective and
subjective scales of evaluation and have been discussed in terms of their respective advantages and disadvantages. It is clearly
evident that some rather primitive techniques can perform well as well as techniques based on a hybrid of various domains can
significantly boost the information fusion rate
