Абстрактный

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).