Comparative Study of Different Image fusion Techniques

Abstract Image Fusion is one of the major research fields in image processing. It is a process of combining the relevant information from a set of images, into a single image, without the introduction of distortion wherein the resultant fused image will be more informative and complete than any of the input images. Image fusion techniques can improve the quality and increase the application of these data. This paper discusses some of the existing image fusion techniques for image fusion like the Averaging Method, Select Maximum/Select Minimum, Discrete Wavelet transform based fusion and Principal component analysis (PCA) based fusion and gives their comparative study together. This report also gives evaluation techniques used to evaluate fused images along with the applications of image fusion.