• Hema P. MenonEmail author
  • K. A. Narayanankutty
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 530)


Image fusion has been extensively used in the field of medical imaging by medical practitioners for analysis of images. The aim of image fusion is to combine information from different images in the output fused image without adding artefacts. The output has to contain all information form the individual images without introducing artifacts. In images that contains more textural properties, it will be more effective in terms of fusion, if we include all the textures contained in the corresponding individual images. Keeping the above objective in mind, we propose the use of Gabor filter for analysing the texture, because under this method the filter parameters can be tunned depending upon the textures in the corresponding images. The fusion is performed on the individual textural components of the two input images and then all the fused texture images are combined together to get the final fused image. To this the fused residual image obtained by combining the residue of the two images can be added to increase the information content. This approach was tested on MRI and CT images considering both mono-modal and multi-modal cases and the results are promising.


Image Fusion Gabor Filters Texture Analysis Magnetic Resonance Imaging (MRI) images Computed Tomography (CT) images Fusion Factor Fusion Symmetry Renyi Entropy 


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© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAmrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita UniversityCoimbatoreIndia
  2. 2.Department of Electrical Communications and EngineeringAmrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita UniversityCoimbatoreIndia

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