Comparative Review on Image Fusion Techniques

Abstract

The goal of image fusion is to combine relevant information from two or more images of the same scene of the different times. The result of image fusion is a new fused image which is more suitable for human being and machine discernment for further image-processing tasks like segmentation, feature taking out and object recognition. Image fusion is the combination of two or more different images to form a new image by using a certain algorithm to obtain more and better information about an object or a study area. The image fusion is mainly done in two domains: spatial domain and transform domain. And in this, two-domain image fusion is performed at three different processing levels which are pixel level, feature level and decision level according to the stage at which the fusion takes place. This depends on the application. There are many image fusion methods that can be used to produce high-resolution multispectral images from a high resolution panchromatic image and low-resolution multispectral images. In this paper, the authors have taken some image fusion techniques and given brief intruder part and compare it as per the performance.

Keywords: Image fusion, principal component analysis (PCA), intensity-huesaturation (IHS), discrete wavelet transform (DWT), curvelet transform