Open AccessA New Algorithm for Image Fusion to reduce computational Time
Author(s) -
Navjot Kaur,
Navneet Kaur
Publication year - 2016
Publication title -
international journal of computer and technology
Language(s) - English
Resource type - Journals
ISSN - 2277-3061
DOI - 10.24297/ijct.v15i4.3979
Subject(s) - image fusion , algorithm , wavelet transform , artificial intelligence , peak signal to noise ratio , image (mathematics) , pixel , top hat transform , image resolution , fusion , block (permutation group theory) , computer science , wavelet , computer vision , mathematics , pattern recognition (psychology) , image processing , feature detection (computer vision) , linguistics , philosophy , geometry
Image fusion is a process to combine two or more images so that fused image becomes more informative than input images. Fusion process provides the spectral and spatial information of image. But main problem occurs of computational time when high resolution images are fused. So this paper describe a new algorithm that is based on wavelet transform in which transform is applied after forming the image into different blocks. This algorithm divides the complete image into different blocks andthen comparing the images by finding the mean square error.By using the threshold value wavelet transform is applied to require block. The transformed blocks are fused by using different fusion algorithms like averaging method, maximum or minimum pixel replacement fusion algorithm. By applying inverse of wavelet transform fused image is constructed which is more informative than the input images. The quality of fused image is find out by comparing the fused image by the original image by finding mean square error and peak signal to noise ratio. The whole process of fusion is applied on the complete image and also by using blocking method then by finding the time parameters it can be conclude that the proposed algorithm reduces the computational time by 10 times to the existence method.