Image fusion using eigen features and stationary wavelet transform

Abstract

Image fusion is a technique of fusing multiple images for better information and more accurate image compared source images. The applications of image fusion in modern military, multi-focus image integration, pattern recognition, remote sensing, biomedical imaging etc.In this paper discussed, pros and cons of various newly arrived existing techniques in spatial and transform domain image fusion techniques. The individual advantages of Stationary Wavelet Transform (SWT) and Principal Component Analysis (PCA) is become great advantage to the proposed method.Standard dataset is used to evaluate the performance of proposed method, the obtained results are compared with exiting methodologies and shows robustness in terms of entropy, standard deviation and Peak Signal to Noise Ratio (PSNR).