Medical image fusion defines the process of fusing two similar medical images to create a single image which is rich in information. The medical image fusion is done to enhance the quality of diagnosis and treatments. This paper introduces a novel image fusion approach HSWGWO (Hybridization of State Transition with Grey Wolf Optimization) for medical images such as MRI, SPECT, PET, and CT images etc. The objective of this work is to overcome the issues of traditional GWO based image fusion technique. In this work, the SWT mechanism is used to extract the features from the input images and then the hybrid mechanism i.e. GWO and ST are applied for fusing the images. The proposed work is compared with the traditional techniques. The comparison is done by considering the sets of various images such as MRI-SPECT, MRI-PET, and MRI- CT images. After analyzing the proposed work is found to be effective and efficient than the traditional image fusion techniques.

Medical Image Fusion, Magnetic Resonance, Transform Domain, Spatial Domain, Frequency Domain

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