Pixel based Medical Image Fusion Techniques using Discrete Wavelet Transform and Stationary Wavelet Transform

Abstract

Background: Process of combining significant information from 2 or more images to get an output without any artifact or information loss. Also to perceive all information required for accurate diagnosis and to get high spatial resolution with functional and anatomical information. Methods: DWT and SWT are used with biorthogonal 2.6 and db1. Average fusion rule is applied for fusing low frequency coefficients and for high frequency coefficients region energy rule is applied. Results: Eight sets of real time medical images are used for the analysis. Comparing the fusion of SWT with DWT, Stationary wavelet transform method performs well than the Discrete wavelet transform as the information loss occurs due to down sampling in each of the DWT sub bands which caused in the relevant sub bands are minimized by SWT. Application: Easy to diagnose for a physician in the field of biomedical.Keywords: Discrete Wavelet Transform, Performance Measures, Stationary Wavelet Transform