Image Fusion - A new hybrid technology

Abstract

Image fusion is considered as one of the best techniques in order to decrease uncertainty and limit redundancy. It is a method of obtaining new image which will contain the data of the previous images in a way which will be more efficient and informative. Until now the image fusion techniques resembled Discrete Wavelet Transform (DWT) or pixel based. This paper will mainly look for the implementation of combining the two separate techniques of image fusion. Stationary wavelet transform (SWT) is a wavelet transform algorithm designed to overcome the difficulties faced by the DWT. Principal Component Analysis (PCA) is a method that uses the technique of orthogonal transformation to develop a new image which has all the properties of the previous images and has its two major dimensions called as the principal components. Therefore, to get rid of the demerits of the prior methods used for fusing of two images another new method is recommended that works by combining the SWT and .PCA This hybrid method is proposed to obtain a superlative, efficient and a superior image as compared to the results or pictures obtained from the pre-existing methods. The picture obtained after using this new method will be of the advanced level and superior than the standard techniques. When compared with the results of the pre-existing techniques we observed that the mean squared error was just 8694.1543 and the other errors were also reduced to a significant value which has been mentioned in detail in results the section.