A Novel Architecture of Medical Image Fusion
Based on YCbCr-DWT Transform
Behzad Nobariyan1, Nasrin Amini2, Sabalan
Daneshvar3, and Ataollah Abbasi4
1Faculty of Electrical Engineering, Sahand
University of Technology, Iran
2Faculty of Biomedical Engineering, Islamic
Azad University Branch of Science and Research, Iran
3Faculty of Electrical and Computer
Engineering, University of Tabriz, Iran
4Faculty of Electrical Engineering, Sahand
University of Technology, Iran
Abstract: 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,
Laplacian-pyramid, Contourlet and DWT.
Keywords: YCbCr, DWT, PET, SPECT, image fusion.
Received April 24, 2015; accepted March 9, 2016
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