A vectorial minimized surface regularizer based image registration model and its numerical algorithm.

• A new image registration model is proposed. • An effective numerical method is proposed to solve the new model. • Numerical experiments show that our new model has good performance. In this paper, we propose a vectorial minimized surface regularizer based image registration model which is suitable for smooth and non-smooth registration. In order to avoid the mesh folding phenomenon, inequality constraint on transformed Jacobian matrix determinant is imposed. In addition, we use Lagrange multipliers combining Gauss-Newton method with Armijo line search with the multilevel method to solve the corresponding model. And guided filter is utilized on the displacement field before and after the registration of each level to avoid noise and preserve the edge information of the image. Furthermore, the convergence analysis of the algorithm is given. Finally, numerical experiments using both synthetic and realistic images are carried out to show the robustness of the proposed model and the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]