Image Registration using Fourier-Mellin Transform with Implementation Guidelines

This article explores the implementation of image registration using the Fourier-Mellin transform. The registration process begins with aligning two images, where the Fourier-Mellin transform serves as a robust method for handling scale, rotation, and translation differences. Key implementation steps include: 1. Preprocessing: Images undergo scaling, rotation, and translation adjustments using interpolation algorithms like bicubic interpolation for scaling and affine transformations for rotation/translation 2. Fourier-Mellin Transform Application: The core algorithm involves converting images to log-polar coordinates followed by Fourier transform computation, enabling invariant feature extraction through phase correlation techniques 3. Post-processing: Registered images require validation using similarity metrics (SSIM, MSE) and refinement through iterative optimization algorithms The implementation typically utilizes key functions such as: - fft2() for 2D Fourier transforms - imresize() with appropriate interpolation methods - imrotate() for angular corrections - Phase correlation algorithms for displacement detection These systematic steps ensure accurate image comparison and registration results, making the Fourier-Mellin transform particularly effective for medical imaging, remote sensing, and computer vision applications.