PERFORMANCE ASSESSMENT OF FUZZY AND NEURO FUZZY BASED ITERATIVE IMAGE FUSION OF MEDICAL IMAGES

摘要

Medical image fusion is a significant job to regain an image which delivers as much as evidence of the same body part at the similar time it also assistances to decrease the storing capability to a particular image. In this paper an assessment is completed between conventional image fusion methods; principal component analysis (PCA), discrete wavelet transform (DWT) and the projected fuzzy and neuro fuzzy based iterative image fusion techniques. The proposed method fuses images based on fuzzy inference system (fis) prepared. Experimentations have been finished on two different sets of multimodal medical images of brain. The projected technique is perceivably and significant related with the present approaches. For the assessment of the projected image fusion technique ten diverse measures is prepared and utilized of, namely Image Quality Index (IQI), Mutual Information Measure (MIM), Fusion Factor (FF), Fusion Symmetry(FS), Fusion Index (FI), Root Mean Square Error (RMSE), Peak Signal To Noise Ratio(PSNR), Entropy(E), Correlation Coefficient (CC) and Spatial Frequency (SF). Assessment outcomes demonstrated that the projected image fusion technique mechanisms improved than any of the conventional image fusion techniques.