Performance Analysis And Working Principle Of Different Image Fusion Models For Remote Sensing Data

Abstract

Image Fusion is a process of combining multiple input images into a single output image. The role of Image Fusion is demanding in many domains like Medical, Satellite, military, Multi focus etc. In remote sensing applications, the increasing availability of space borne sensors gives a motivation for different image fusion algorithms. Several situations in image processing require high spatial and high spectral resolution in a single image. The remote sensors extract desired information about the Earth's surface structure and content, which is derived from different portions of the electromagnetic spectrum at a distant location vary in spectral, spatial and temporal resolutions  The limitation of satellite sensors is that they cannot directly collect high-resolution multispectral images. However, they provide PAN and MS sensors simultaneously. So there is need for image fusion. Fused products have more advantage than normal product. In this paper, different image fusion methods and their performance have been analyzed for choosing the right model for image fusion.