Image fusion is the process of conflating or combing two or more images into a single image in order to implicate the necessary information from the source images. There is plenty of technological advancement present in today’s medical imaging field. The main drawback is that each and every imaging modality has its own specialty and limitation. Thus, fusion is used to overcome the shortcoming of displaying vital information in multiple images. CT images would manifest the clear pictures of hard tissue like bone structures but MRI images exhibits the soft tissue. When physician analyze the images where some of the information may not be viewed properly, the proposed methodology helps to extract more features from the images in addition to the boundary analysis carried out to identify the particular portion of the images. The discrete wavelet transform (DWT)of coiflet(COIF) and discrete meyer wavelet(DMEY) applied to the images which decompose the images and the wavelet coefficient of low pass and high pass filters of both images are identified and adjusted to the optimum contrast for a better elucidation. The inverse DWT(IDWT) helps to reconstruct the images by reverse operation of DWT. two input images are fused using Left-Right (LR), Right-Left (RL), Up-Down (UD), Down-Up (DU) methods. The features and results of the above methods are explored and compared with COIF and DMEY.