| Abstract: | In this paper, a fast algorithm for Euler's elastica functional is proposed,in which the Euler's elastica functional is reformulated as a constrainedminimization problem. Combining the augmented Lagrangian method and operatorsplitting techniques, the resulting saddle-point problem is solved by a serialof subproblems. To tackle the nonlinear constraints arising in the model, a novelfixed-point-based approach is proposed so that all the subproblems either is alinear problem or has a closed-form solution. We show the good performance of ourapproach in terms of speed and reliability using numerous numerical examples onsynthetic, real-world and medical images for image denoising, image inpaintingand image zooming problems. |
