www.rspsciencehub.com Volume 02 Issue 08 August 2020 International Research Journal on Advanced Science Hub (IRJASH) 34 A Review on Decomposition/Reconstruction methods for Fusion of Medical Images Harmeet Kaur 1 , Satish Kumar 2 1 Research Scholar Department of Computer Science and Applications, Panjab University, Chandigarh, India. 2 Associate Professor Department of Computer Science and Applications, Panjab University, SSG Regional Centre Hoshiarpur, Punjab. Abstract An image contains variety of information (in terms of frequency i.e. low and high) and to split that information into sub-parts, Decomposition of image is done so as to extract the desired features present in the image. On decomposing the image, it gets divided into sub-images. Each sub image will contain different information. The coarsest information is fetched in the decomposition phase. The aim of Fusion process is to bring out the best information from the base images. The Fusion technique is applied on the decomposed sub-images obtained from each source image. After successfully fusing the sub-images, single fused image is obtained after applying the reconstruction method on the fused sub-images Keywords: Multi-modality, Decomposition, Fusion, Laplacian, Wavelet 1. Introduction Fusion of images combines related information from multiple images and produces an image. Combining the images should reduce the redundancy, without distortion. The output image is useful for visual insight and interpretation. According to J. Du(Du, Li, Lu, et al. 2016), Multi- modal medical image fusion is the combination of multiple images from single/multiple imaging modalities. Medical image fusion leads to improved image quality while preserving the important features. Fused output images are used in clinical applications and gives better outcome for diagnosis, assessment of disease, etc. The medical images varies highly in their modality like CT ( Computed Tomography) gives anatomical information, MRI ( Magnetic Resonance Imaging) gives soft tissue contrast information and PET( Positron Emission Tomography) is an radionuclide technique which provides functional information. Fusing the modalities will result in a merged image containing the best information from both the modalities. In this paper, the state of the art decomposition/reconstruction methods are studied. This is followed by summarization of these methods. At last, this review paper concludes that while many decomposition/reconstruction methods have been anticipated, there still exist several future directions to select a method. Rest of the paper is organized as follows, Section 1 contains the introduction of Fusion and the various modalities available, Section 2 contain the work flow of Fusion method including various phases, Section 3 contain Decomposition/Reconstruction methods categorized as Pyramid, wavelet and color based Decomposition/Reconstruction methods., Section 4 contain the summary of the methods available for Decomposition/Reconstruction and Section 5 concludes research work with future directions. 2. Multi-Modality Medical Image Fusion Images (Multi-Modality) are acquired and are pre-processed (if needed) to make it suitable for fusion. The acquired images are proceeded to