A Detailed Literature Survey and Analysis of Different Image Fusion Methods for Remote Sensing Data

Abstract

The goal of image fusion is the extraction of desired information from the image. The electromagnetic energy arising from the scene's spectral, spatial, and temporal variation contains our desired information. However one image does not contain all the information. So we combine one or two images with fusion. By fusion we get the desired results. But this has been a challenge for a long time to find out best appropriate algorithm to get highest results from the fused image. It is possible to merge both data and produce images with the best properties of each, particularly high spatial and spectral resolution, using proper algorithms. This is referred to as pan sharpening and is a type of multisensory data fusion.  There are different types of fusion methods. In this paper development of different fusion methods over the time and their advantages and disadvantages are discussed and analyzed.