MATLAB Implementation of Fourier Transform for Image Registration

Using Fourier transform to perform image registration in the frequency domain constitutes a relatively new registration methodology. However, for elastic registration applications, the effectiveness remains suboptimal and necessitates additional research and refinement. The implementation typically involves MATLAB functions like fft2() for 2D Fast Fourier Transform, fftshift() for frequency domain centering, and phase correlation algorithms to determine displacement vectors between images. Future research directions should explore alternative registration algorithms and techniques to enhance the accuracy and stability of elastic registration. Additionally, integrating complementary image processing methodologies such as feature extraction using corner detectors (e.g., Harris corner detection) and machine learning approaches (e.g., convolutional neural networks) could further improve registration outcomes. These investigative advancements and methodological improvements will contribute to the progression of registration technologies and provide more robust registration solutions for practical applications.