A Novel Architecture of Medical Image Fusion Based on YCbCr-DWT Transform

Image fusion is one of the most modern, accurate and useful diagnostic techniques in medical imaging. Mainly, image fusion tries to offer a method for solving the problem that no system is able to integrate functional and anatomical information. Multiple image fusion of brain is very important for clinical applications. Positron Emission Tomography (PET) image indicates the brain function and Single-Photon Emission Computerized Tomography (SPECT) indicates local performance in the internal organs like heart and brain imaging. Both of these images are multi-spectral images and have a low spatial resolution. The Magnetic Resonance Imaging (MRI) image shows the brain tissue anatomy and contains no functional information. A good fusion scheme should preserve the spectral characteristics of the source multispectral image as well as the high spatial resolution characteristics of the source panchromatic image. There are many methods for image fusion but each of them has certain limitations. The studies have shown that YCbCr preserves spatial information and Discrete Wavelet Transforms (DWT) preserves spectral information without distortion. The proposed method contains the advantages of both methods and it preserves spatial and spectral information without distortion. Visual and statistical analyses show that the results of our algorithm considerably enhance the fusion quality in connection with: discrepancy, average gradient and Mutual information; compared to fusion methods including, Hue-Intensity-Saturation (HIS), YCbCr, Brovey, Laplacianpyramid, Contourlet and DWT.