Image Fusion-based Multi-frequency Microwave Tomography

In this research study, an investigation of the benefit of wavelet-based image fusion algorithm for enhancing the quality of the reconstructed images in a multi-frequency microwave tomography was conducted. The microwave tomography system which consists of a PocketVNA, a pair of Vivaldi antenna and a set of Arduino-based electromechanical system was used to acquire the scattering wave around an object being observed. The electromechanical was used to move the angular positions of the Vivaldi antenna pair in the scanning process in order to measure the reflection coefficient (S11), magnitude and phase of the microwaves interacted with observed object material. The Vivaldi antenna works in the range of 1.5 – 9.0 GHz, while the PocketVNA operates in range of 500 kHz - 4 GHz. Experiments were done to test the performance of the system with types of materials of different shapes and sizes. The reflection coefficient data (S11) resolved and reconstructed into an image via MATLAB based on Born approximation reconstruction algorithm. Image reconstruction per single frequency is done sequentially from low frequency to high frequency, with a total of 6 different frequency values. A multi-frequency approach will be done by combining the element of stability from the effect of using low frequencies and high-resolution element from the effect of relatively higher frequency usage. The use of multi-frequency reduces nonlinearity problem and increases the stability to get an optimal image reconstruction. The used image fusion algorithm was also tested using the datasets from Fresnel Institute in order to verify its performance. The image yielded from the image fusion algorithm has a significant increasing image quality compared to the individual images from the reconstruction process resulted on single frequency usage without the image fusion process.