Semi-automatic image registration using harris corner detection and RANdom SAmple Consensus (RANSAC)
Image registration is a fundamental image processing task to match and align physically two images which could have been imaged by different sensors, view angles and or at different times. This paper presents a new algorithm for image registration based on a combination between cross correlation function and feature-based methods .In the proposed algorithm, the ground control points are extracted from input images using the Harris corner detector, and the correspondence between the points extracted from the different images is established using RANdom SAmple Consensus (RANSAC) method with. The image coregistration in this paper is performed by three ways: It is first performed by the proposed algorithm then it is performed by feature-based methods and finally the results are compared with those achieved using Gamma design software. The method is also evaluated by using the coherence map. The results showed that the combination between cross correlation function and feature-based methods almost give us the same results of traditional method but with low processing time., which is our aim to prove and validate. (4 pages)