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IMAGE FUSION ALGORITHMS USING DIFFERENT WAVELET METHODS AND IMPROVEMENT TECHNIQUES

B.Ragavendhra Reddy, Dr.T. Ramashri

Image fusion is the process of combining the relevant information from two or more images into a single highly informative image. The resulting fused image contains more information than the input images. In this paper, different methods for fusing different modality of images [e.g., MRI, CT; MULTI-SPECTRAL, PANCHROMATIC etc.] and comparison of all these methods are presented. In addition to this, image fusion improvement technique also presented. The methods presented here are Simple Averaging Method, Principal Component Analysis [PCA] method, different wavelet transform methods and integrating these wavelet methods with PCA method. The wavelet Transform methods used here are Symlet Wavelets, Bi-Orthogonal wavelet, discrete Meyer wavelet, Reverse Bi-Orthogonal wavelet methods etc. The Fusion results obtained from above methods are evaluated and compared according to the measures Mean, Standard Deviation, Entropy (H) , Correlation Coefficient(CC), Co-Variance, Root Mean Square Error(RMSE), Peak Signal To Noise Ratio(PSNR).