Image fusion on different modalities using multiwavelet transforms

Image fusion is a process of combining the complementary information from two or more images into a single highly informative image. The resulting fused image contains more information than both the input images. In this paper MWT algorithm for fusing two different modality medical images and different quantitative metrics are calculated. Qualitative metrics for resultant image such as entropy, standard deviation are calculated. The images obtained from different medical imaging techniques such as Computer Tomography (CT), Positron Emission Tomography (PET) images are fused into a new image The CT image can provide dense structures like bones and implants with less distortion, but it cannot detect physiological changes, while the PET image can provide functional details of cancer to improve the information quality. In the present fusion algorithm, the input images from two different modalities are initially registered and then transform namely Multi-Wavelet transform is applied on the input images. Finally the resultant images are fused using various fusion techniques.