Image registration using Adaptive Polar Transform

Image registration is an essential task in many image processing applications. Log-polar transform (LPT) is a well known tool for image processing for its rotation and scale invariant properties. However it suffers from nonuniform sampling which makes it not suitable for the environment when registered images are altered or occluded. Inspired by LPT, this paper presents a new algorithm that addresses the problems of the conventional LPT while maintaining the invariant properties. We introduce adaptive polar transform (APT) technique and an innovative matching mechanism that serve as image processing tool for recovering scale and rotation change of the registered image. Unlike the conventional LPT that focuses only at the fovea area of the registered image, our proposed APT gives even consideration to the entire image. Translation of the registered image is recovered with the new search scheme by using Gabor feature extraction to accelerate the localization procedure. The experimental results indicate that our proposed method outperforms conventional LPT in registering images that are altered or occluded.