Implementation of Hybrid Algorithm Based on NSCT for Medical Image Fusion
A. S. Srinivasa Rao1, M. Bala Krishna2, P. Sirish Kumar3, Ch. Chandrika4, Jaganmohan Rao. T5
1A. S. Srinivasa Rao, Department of Electronics & Communications Engineering, Aditya Institute of Technology and Management, Tekkali, Srikakaulam (Andhra Pradesh), India.
2M. Bala Krishna, Department of Electronics & Communications Engineering, Aditya Institute of Technology and Management, Tekkali, Srikakaulam (Andhra Pradesh), India.
3P. Sirish Kumar, Department of Electronics & Communications Engineering, Aditya Institute of Technology and Management, Tekkali, Srikakaulam (Andhra Pradesh), India.
4Ch.Chandrika, Department of Computer Science & Engineering, Sarada Institute of Technology and Management, Ampolu, Srikakaulam (Andhra Pradesh), India.
5Jaganmohan Rao. T, Department of Electrical & Electronics Engineering, Aditya Institute of Technology And Management, Tekkali, Srikakaulam (Andhra Pradesh), India.
Manuscript received on 22 November 2019 | Revised Manuscript received on 10 December 2019 | Manuscript Published on 30 December 2019 | PP: 86-92 | Volume-9 Issue-2S3 December 2019 | Retrieval Number: B10211292S319/2019©BEIESP | DOI: 10.35940/ijitee.B1021.1292S319
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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: The process of combining the two different modal images into one single image is multimodal image fusion. The resulting image is helpful in the medical field for effective and better detection of disease and the processing of images; surgery, tumor recognition, illnesses, etc. In the only modes of medical images, the merged image attributes cannot be achieved and can be overcome with the image fusion of various modal images. A new hybrid algorithm for directive multimodal image fusion will be built for this paper based on the non-sub-sampled contourlet transformation. The images will be fuse through the use of the proposed techniques and comparison with existing technological techniques, using quantitative and qualitative measures. MRI and positron-emission tomography (PET) are used. Quantitative steps, like the Entropy (EN) and Structural Similarity Index (SSIM), will be taken to verify the algorithms.
Keywords: Entropy Fusion, Image, NSCT, SSIM.
Scope of the Article: Image Security