Analysis of Metric based Wavelets for Medical Image Fusion

Abstract

Image fusion is the process in which two or more images are combined to a single image which contains the detailed information compared to the individual source or input images, for the fusion of medical images the Discrete Wavelet Transform is used. In this paper two medical images such as CT and MRI images are fused using an algorithm. The different wavelets like haar, db2, coif1, sym2, fk4, dmey, bior1.1 and rbio1.1 are used to fuse the medical images, the performance of all these wavelets are measured in terms of evolution metrics such as Standard deviation, Average gradient and Edge Strength, based on the comparative analysis for a particular evaluation metric a specific wavelet to be considered to obtain the better results among all the wavelets.

 Keywords: DWT, CT, MRI, Image Fusion, Average Gradient, Standard Deviation, Edge Strength.