Aerial image registration using Projective Polar Transform

Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration or analysis. Recently researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, the accuracy of the approach limits by the number of samples used in the mapping process, which affects directly the computational cost. Motivated by the success of LPT based approach and its limitation, we propose a novel projective polar transform (PPT) based image registration method that is robust to translation, scale, and rotation and yields high accuracy while requires low computational cost. Unlike LPT that 2D interpolation is needed in the mapping process, our method uses one-to-one mapping mechanism that directly arranges image from Cartesian to polar coordinate according to pre-computed PPT map. An innovative projection mechanism is proposed to reduce the image from two to one dimensional vectors. With the proposed approach, the mapping procedure is accelerated and the matching process can be performed in 1D. This results in great reduction of the computational cost.