A Review on Spatial and Transform Domain Image Fusion Methods

Abstract

Image fusion aims to collect better information from an image obtained by combining two or more different images. Image fusion has many applications such as remote sensing, medical imaging, medical diagnosis, robotics, surveillance, and image enhancements. This article presents the strengths and weakness of recent arrivals in the literature on spatial and transform domain. A comparative analysis among recently existed literature of various types of image fusing methodologies. A generalized flow diagram for image fusion which is universally acceptable to all types of images such as medical images, visible images, infrared images, multi-focus images, multi-exposure images, hyperspectral image and multispectral images is depicted. Various effective qualitative and quantitative performance measures useful for image fusion with reference image and without reference image are also tabled. At last, recommendations are given as per current research requirements for better performance with decent complexity.