Multiple MRI Image Fusion using Normalized Principal Components of DWT Subbands
This paper proposes a fusion algorithm based on principal component averaging and discrete wavelet transform for multiple magnetic resonance (MR) images. Principal components are evaluated for the covariance matrix of three or more source images of MR T1 and MR T2 modes. Normalized Eigen values of the covariance matrix of the source images contribute linear weights for the fusion rule. This fusion algorithm provides a meaningful replacement for viewing multiple MR images by means of a composite fused image. Image fusion is carried out for the three and four source image combinations. Performance of the fusion algorithm is evaluated using fusion factor, average quality index and figure of merit. The evaluated metrics sufficiently prove that the proposed fusion method delivers better fusion outcomes for the fusion of four source images.
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