A Survey on Image Fusion Requirements, Techniques, Evaluation Metrics, and Its Applications

Abstract

Fusion refers to combining two or more distinct things, the main objective of employing fusion is to generate results that provides the most detailed, reliable and accurate information possible. The image fusion is one of the main branchof data fusion. In image fusion the images are fused at different levels of images like pixel, feature and decision level. The necessity of image fusion for high resolution on multispectral and panchromatic images or realtime images for better vision. This paper reviews the general requirements of image fusion, widely used image fusion techniques such as PCA,IHS,DWT,NSCT etc.,summarizes the Quality Assessment Metrics in terms of metric, description and its principle, finally image fusion applications in various fields such as object detection, object identification, optimization and pattern reorganization, medical imaging, etc.,

Recent Advancements in Multimodal Medical Image Fusion Techniques for Better Diagnosis: An Overview

“…Three levels of operations are performed in image fusion techniques [15,16]. In the pixel level, the images of individual pixels are directly combined.…”

Multimodal medical image fusion in NSST domain with structural and spectral features enhancement

“…All MMIF are categorized into three levels: decision level, pixel level, and feature level [ 5 , 6 ]. However, structural and spectral enhancement deals with pixel information.…”