Algorithm For Multi-modality Medical Image Fusion Based On Wavelet Transform

Now, the rapid development of science and technology, driven by computer technologyand medical imaging. appeared in a variety of advanced imaging equipment.，provides betterclinical diagnostic services. But each modality images have errors, medical image fusionhave full advantage of multi-modal images, get their complementary information,fused imagehas richer details. Therefore, medical image fusion rapid development.Which image fusionmethod selection becomes a problem to be solved.This selection is the image fusion methodbased on wavelet transform.Firstly, the paper introduced the background and significance of topics、the situationdomestic and abroad, then introduced the classification、method and criteria of the imagefusion.Including the basic theory of wavelet analysis、 two-dimensional image waveletdecomposition and wavelet transform for the steps of medical image fusion.Describes the characteristics of different wavelet basis function and different fusionrules.Discuss the effects of different wavelet function, and different fusion rules on fusionimage quality. And a large number of simulations to obtain the relevant conclusions;Coif5,Db3in CT and MRI medical image fusion performance is better.Regional variance methodcan retain most of the details information of the source image.Enhance the effectiveness andquality of the image fuse to some extent.Finally, introduction and research Contourlet transform theory and wavelet-Contourlettransform theory, and conducted simulation experiment. Concluded: Image fusion methodbased on wavelet-Contourlet transform can reaction visual effects of image more accuratelyand effectively.