Image Fusion Methods and Quality Assessment Parameters

Abstract

Image processing techniques primarily focus upon enhancing the quality of an image or a set of images and to derive the maximum information from them. Image Fusion is such a technique of producing a superior quality image from a set of available images. It is the process of combining relevant information from two or more images into a single image wherein the resulting image will be more informative and complete than any of the input images. A lot of research is being done in this field encompassing areas of Computer Vision, Automatic object detection, Image processing, parallel and distributed processing, Robotics and remote sensing. In this paper, we have described the various 11 fusion methods (IHS, PCA, Pyramid method, Wavelet transform etc.) and the different quality assessment parameter (PSNR, MSE, average difference, NAE etc.) used to assess the quality of the fused image. The various application areas of image fusion are also included in this paper.