The goal of image fusion is to obtain large amount of information into a single image with more quantitatively and qualitatively. The image fusion can be applicable in various fields like multi-focus, multi-modal medical, satellite etc. This paper proposed statistical measurements of Multimodal MRI-PET medical image fusion using 2D Hartley transform (HT) in HSV color space. This proposed method was discussed with two different modalities of medical images like MRI (Magnetic Resonance Imaging) and PET (Positron Emission Tomography) and also discussed with five steps. Initially the PET color image is converted into HSV channels. Second step is MRI and V component of PET image are divided into 8∗8 blocks and then apply 2D Hartley transform on each block of two input images. Third step is compute variance of each block of two images and then select best blocks. Fourth step is applying inverse 2D HT and all blocks are arranged into single image i.e. new V component. Finally concordination of New V component, H, S to get HSV image and then convert HSV to RGB to obtain final fused image with more accurate. The result shows the importance of the proposed image and this is superior to existing methods like DFT along with Smooth, Hartley along with Smooth, Hartley along with Mean, DFT along with Mean and DCT along with Smooth. The evaluation parameters such as Mean, Standard Deviation and Gradient plays a major role in image fusion for testing the quality. © 2019 Procedia Computer Science. All rights reserved.