Image Fusion using Dual Tree Complex Wavelet Transform with Maximum Selection and Multi-scale Edge Fusion of MRI and CT Images

Medical imaging has emerged as one of the promising areas of research as it aims to serve in diagnosing medical related issues with efficient techniques of both spatial and transform domain. Discrete Wavelet Transforms techniques are the most widely used fusion techniques where more than one modality of images considered and combined together to obtain a better image with extra anatomic and functional information. Complex transforms helps to enhance the performances of traditional wavelet transform. In this work, we have adopted Dual Tree Complex Wavelet Transform (DTCWT) and Maximum Selection, and multi-scale edge fusion rules were used along with DTCWT. The results were obtained using MATLAB software and compared with traditional wavelet transforms. The experimentation results showed that DTCWT offered better results.