Image Fusion is a process of combining the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. The goal of image fusion (IF) is to integrate complementary multisensory, multitemporal and/or multiview information into one new image containing information the quality of which cannot be achieved otherwise. It has been found that the standard fusion methods perform well spatially but usually introduce spectral distortion, Image fusion techniques can improve the quality and increase the application of these data. In this Project we use various image fusion techniques using discrete wavelet transform and discrete cosine transform and it is proposed to analyze the fused image, after that by using various quality assessment factors it is proposed to analyze subject images and draw a conclusion that from which transformation technique we can find the better results. In this project several applications and comparisons between different fusion schemes and rules are addressed
