Abstract
Image fusion combines complimentary information from multiple images acquired through different sensors, into a single image. In this paper, an image fusion technique based on Gray wolf optimization is proposed for fusion of medical images, Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET). Firstly, Hilbert transformation is applied to extort the informative data from input images. The relevant part of the input images based on information present, is selected for image fusion. The selected portion of the input images is fused by using Gray wolf optimization based method. The simulation results show improved performance of proposed framework as compared to conventional techniques.
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