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This work is motivated by the potential and promise of image fusion technologies in the multi-sensor image fusion system. The aim of this research is to focus on multi-sensor pixel level image fusion for medical application due to its significance of medical field. Medical fusion methods are only a possible way that able to combine correlating information of multiple images into a single image to explore the possibility of data reduction and improvement of information density. The dissertation explores the possibility of using Stationary Wavelet approach in image fusion and further optimization using Genetic Algorithm and Particle Swarm Optimization. The comparative analysis of Stationary wavelet transform combined with optimization algorithm has been performed with several sets of computed Tomography (CT) scan and Magnetic Resonance imaging (MRI) images using MATLAB. Improve statistics results are obtained in terms of peak signal to noise ratio (PSNR), entropy, root mean square error (RMSE), edge strength, mutual information.
About the author
Dr Reecha Sharma is working as Assistant Professor in Deptt of ECE Punjabi University Patiala, India. She has eleven years of teaching experience. She has published more than 60 research papers in International/ National journals and conferences. She has guided 23 M.Tech students.She has published 7 ebooks. She is professional member of Institute
