Dual Filter Based Images Fusion Algorithm for CT and MRI Medical Images
M.N. Narsaiah1, S. Vathsal2, D. Venkat Reddy3

1M.N. Narsaiah, Associate Professor, Dept of ECE, KG Reddy College of Engineering and Technology, Hyderabad, Telangana, India.
2S. Vathsal, Ex Director, ER & IPR, DRDO, New Delhi, India.
3D. Venkat Reddy, Professor, Department of ECE, MGIT, Hyderabad. Telangana, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 2673-2678 | Volume-8 Issue-9, July 2019 | Retrieval Number I8988078919/19©BEIESP & Sciences Publication | DOI: 10.35940/ijitee.I8988.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A novel image fusion algorithm based on two filters, one is laplacian filter for de-nosing the detailed coefficients and second filter is Guided Filter (GF) used to refine the approximation as well as detailed coefficient for Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) medical images is proposed. Because of using wavelet transform, we obtained approximation coefficient and other three coefficients of CT and MRI images. Now two weight maps are obtained after the process of denoising. Another reason for obtaining two weight maps is because of comparison. Here comparison is done between two approximation coefficient and six detailed coefficients. By using the approximation coefficients and detailed coefficients, GF is designed. Here GF will guide an image corresponding to the weight maps. Here the weight maps are smoothed using GF and this is mainly served as input image. Hence the weighted fusion algorithm will fuse the both CT and MRI images. A pure fused image is obtained only when the CT and MRI images are refined by inverse wavelet transform. From the comparison results, it can observe that the proposed system gives better results compared to existing system. As well as the proposed system will give maximum amount of input in detail manner.
Keywords: Fusion, Guided Filter, Registration, Weighted Fusion, Wavelet Transform, Tumor. Laplacian Filter.

Scope of the Article: Image Security