Comparison of Different-Image Fusion Techniques in Wavelet Domain

Abstract

This paper reviews comparison of different image fusion methods in transform domain. Image fusion is defined as a process of fetching up entire relevant information through multiple photographs and integrating into a single image. This combined image has all the relevant information and is more accurate and informative than any of the original images. The key objective of image fusion is to create a one photograph through all the pertinent data from many images. Hence, compared to any previous photograph, the current one provides a more precise illustration of the arena. The fused picture become more useful and has wide range of application in different areas, so fusion of image is very necessary to find minute information which is present on different picture. The purpose of this paper is to create fused images based on different image fusion techniques and compare the results. Additionally, this paper also provides measurements of quality of the fused images by using two quality indicators namely Peak Signal to Noise Ratio (PSNR), and Mean Square Error (MSE).