Image Registration Using Log Polar Transform and Phase Correlation to Recover Higher Scale
The Journal of Pattern Recognition Research (JPRR) provides an international forum for the electronic publication of high-quality research and industrial experience articles in all areas of pattern recognition, machine learning, and artificial intelligence. JPRR is committed to rigorous yet rapid reviewing. Final versions are published electronically
(ISSN 1558-884X) immediately upon acceptance.
Image Registration Using Log Polar Transform and Phase Correlation to Recover Higher Scale
JIGNESH NATVARLAL SARVAIYA, Dr. Suprava Patnaik, Kajal Kothari
JPRR Vol 7, No 1 (2012); doi:10.13176/11.355 
Download
JIGNESH NATVARLAL SARVAIYA, Dr. Suprava Patnaik, Kajal Kothari
Abstract
Image registration is an important and fundamental task in image processing used to match two different images. Given two or more different images to be registered, image registration estimates the parameters of the geometrical transformation model that maps the sensed images back to its reference image. In all types of image registration, robustness of the algorithm is the main and required goal. Image registration is the process of spatially aligning two or more images of a scene taken at different times or with different sensors or from different viewpoints. This basic capability is needed in various image analysis applications which include remote sensing, medical image analysis, object recognition, etc. In this paper, we have proposed an algorithm that is based on Log polar transform and phase correlation to register images which are transformed by rotation, translation and higher value of scale. The proposed algorithm can recover scale value up to 4. The robustness of this algorithm is verified on different images with similarity transformation, partial data and in the presence of noise.
Keywords : Image Registration, Log-Polar Transform (LPT), Fast Fourier Transform
JPRR Vol 7, No 1 (2012); doi:10.13176/11.355 | Full Text  | Share this paper: