An efficient approach for Image fusion technique using different transform methods
Image fusion is an important aspect for medical diagnostics and treatment. It is created by combining information from multiple modalities which can provide the most common information of both physiological and anatomical with high spatial resolution which is used for clinical diagnosis and therapy purpose. In the normal fusion rule method, it is calculating the average value of a gray scale which produces less quality of an image these results in poor diagnostics. In this paper, an efficient fusion algorithm is developed by calculating the highest coefficient from each sub-band and is performed by combining pairs of Computed Tomography (CT) and Positron Emission Tomography (PET) image of abnormal liver to locate the tumour for better diagnostics. The proposed fusion scheme is compared with different transform methods like Wavelet transform (WT), Stationary Wavelet transform (SWT), Non-Sub Sampled Contourlet transform (NSCT) and Complex Contourlet transform (CCT). Experimental result shows that the proposed fusion algorithm for CCT provides the best performance when compared to other transform methods.
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