Abstract: Image fusion is a process of blending the complementary as well as the common features of a set of images, to generate a resultant image with superior information content in terms of subjective as well as objective analysis point of view. The ultimate aim of medical image fusion can be broadly defined as the combination of visual information contained in any number of input medical images into a single fused image without introducing distortion or information loss. This paper gives a the most efficient method to serve the fusion purpose. The objective of this proposed method is to develop a novel image fusion algorithm and its applications in biomedical field such as in image-guided surgery and radiotherapy with efficient and true diagnosis.
Keywords: Computerized tomography Scan(CT), Magnetic resonance imaging(MRI), Positron emission tomography(PET), Discrete wavelet(DWT), Stationary wavelet(SWT), Dual-tree complex wavelet(DTCWT), Contourlet (CT), Principal Component Analyses(PCA), Pulse coupled neural network(PCNN), Nonsubsampled Contourlet (NSCT), Shearlet transform(SHLT).