Systematic Review and Analysis of Various Multi-Focus Image Fusion Techniques

Abstract

Nowadays, the wide range of real-time applications like remote sensing, photography, video surveillance, medical imaging, dynamic processes, astronomy, machine vision, etc. in which the image fusion used. An important example fusion of image in photography application is Multi-focus Image Fusion (MIF). Image fusion utilized to collect vital image data through several input pictures and consolidate into a single image such a way that it consists of complete data of input images. Due to the wide range of image fusion applications, it gains significant researcher's attention from the last three decades. Recently due to technology advancement and high-dimensional imaging, designing robust and efficient MIF solutions with minimum computation efforts is a challenging research study issues. This paper presents the systematic study and analysis of various MIF methods under the different categories to consolidate the benefits and research study issues. The main motive of this study is to present study over the MIF in two key aspects such as MIF solutions and MIF performance evaluation parameters. In this paper, we reviewed MIF solutions introduced during the last once decade mainly in three categories such as fusion in the domain of special, transform domain fusion & fusion in the deep learning domain. Study of various objective evaluation parameters and their significance to evaluate any MIF technique discussed. The outcome of this paper is the current progress in MIF domain, the problems in different domains, and possible future directions.