The Successful fusion of images acquired from different modalities is of great important in many applications such as microscopic imaging, remote sensing, robots and medical imaging. Medical image fusion is a technique in which useful information from two or more registered medical images is integrated into a new image that can be used to make clinical diagnosis and treatment more accurate. This paper proposes fusion of magnetic resonance and computed tomography medical images using Haar wavelet and principal component analysis (PCA). The wavelet transform is applied to decimate the each source image. The obtained decimated coefficients of source images are evaluated using principal component analysis. The resulting Coefficients are fused and reconstructed using inverse wavelet transforms. we applied number wavelets for the fusion process. The comparative analysis is made based on MSE & PSNR.

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Fusion Haar Wavelet Pca