Columbia International Publishing American Journal of Algorithms and Computing (2013) Vol. 1 No. 1 pp. 39-49 doi:10.7726/ajac.2013.1003 Review ______________________________________________________________________________________________________________________________ *Corresponding e-mail: skchakarvarti@gmail.com 1 Faculty of Engineering & Technology, Manav Rachna International University, Faridabad, India 1* Research & Development Cell, Manav Rachna International University, Faridabad, India 2 Faculty of Engineering & Technology, Jamia Millia Islamia University, New Delhi, India 39 Image Registration Methods: A Short Review Sunanda Gupta 1 , S. K. Chakarvarti 1* , and Zaheerudin 2 Received 4 September 2013; Published online 14 December 2013 © The author(s) 2013. Published with open access at www.uscip.us Abstract The purpose of this paper is to provide a review of classic as well as recent image registration methods. Image registration method aims to align two or more images of the same scene taken at different times, with different instruments, from different viewpoints. In this process two images (the reference and sensed images) are geometrically aligned. The reviewed approaches are classified according to four basic steps of the image registration procedure: feature detection, control points matching, a design of the mapping function, and image transformation and according to their nature (area based and feature-based). The paper also has an objective to provide a comprehensive study of different image registration methods, regardless of particular application areas. Keywords: Image registration; Feature detection; Feature matching; Mapping function; Resampling; Area based registration 1. Introduction Image registration is one of the most important image processing applications of geometric transformation. It is to find the correspondence between images of the same scene. Many image processing applications like computer vision, medical imaging, and remote sensing require image registration which is a process of overlaying two and more images taken at different times or from different viewpoint, acquired by same/different sensors. To register images, we need to find a geometric transformation function that aligns images with respect to the reference image (Zitova and Flusser, 2003). Rigid, perspective, affine, projective are commonly used geometric transformations in image registration process. A large variety of registration techniques have been studied for different kind of applications in past years. The objective of this paper is to distinguish between image variations and registration method applied for the particular variation in the image.