A Novel Iterative Rigid Image Registration Algorithm Based on the Newton Method
J. Khosravi, Mohammad Shams Esfand Abadi, Reza Ebrahimpour · International Journal of Image and Graphics · 2020
In recent years, Image Registration has attracted lots of attention due to its capabilities and numerous applications. Various methods have been exploited to map two images with the same concept but different conditions. Considering the finding of the mentioned map as an optimization problem, mathematical-based optimization methods have been extensively employed due to their real-time performances. In this paper, we employed the Newton method to optimize two defined cost functions. These cost functions are Sum of Square Difference and Cross-Correlation. These presented algorithms have fast convergence and accurate features. Also, we propose an innovative treatment in order to attend to one of the free parameter-rotations or scale as a sole variable and the other one as the constant value. The assignment is replaced through the iterations for both parameters. The intuition is to turn a two-variable optimization problem into a single variable one in every step. Our simulation on benchmark images by the means of Root Mean Square Error and Mutual Information as the goodness criteria, that have been extensively used in similar studies, has shown the robustness and affectivity of the proposed method.