Multimodal Medical Image Fusion Enhancement Technique for Clinical Diagnosis

Image fusion is a process, which collects the important Information from several images and convert it into single image. Now a days image fusion plays a major role in medical image processing. There are many other transforms for the fusion depending on the fusion and input images. In this paper, we have adopted the combination of DWT and Principal component analysis (PCA) image fusion that helps the evaluating of brain tumour detecting tissues and other cancer diseases. Which could not disturbs the information presents in the source input image and it could be more informative after when it undergoes fusion process. The results of this fusion process gives more information that is accurate in final fused image, which helps the doctors for clinical diagnosis. Performance parameters like entropy, mean and standard deviation are also calculated which gives in better fusion results.