Rotation Invariant Registration of 2D Aerial Images Using Local Phase Correlation

Abstract: Aerial image registration requires a high degree of precision. In order to improve the accuracy of feature-based registration, this project proposes a novel Log-Polar Transform (LPT) based image registration. Instead of using the whole image in the conventional method, feature points are used in this project, which reduces the computational time. For rotation invariance, it is not important how the image patch is rotated. The key is focusing on the feature points. So a circular image patch is used in this project, instead of using square image patches as used in previous methods. Existing techniques for registration with Fast Fourier Transform (FFT) always do FFT first and then Log-Polar Transformation (LPT), but it is not suitable in this project. This project does LPT first and then the FFT. The proposed process of this project contains four steps. First, feature points are selected in both  the reference image and the sensed image with corner detector (Harris or SIFT). Secondly, image patches are created using feature point positions as centers. Each point is a center point of LPT, so  circular image patches are cropped choosing a feature point as center. The radius of the circle can be changed. Then the circular images are transformed to Log-Polar coordinates. Next,  the LPT images are dealt with using phase correlation.  Experimental results demonstrate   the reliability and rotation invariance of the proposed method.