TY - JOUR T1 - A Fast Augmented Lagrangian Method for Euler's Elastica Models JO - Numerical Mathematics: Theory, Methods and Applications VL - 1 SP - 47 EP - 71 PY - 2013 DA - 2013/06 SN - 6 DO - http://doi.org/10.4208/nmtma.2013.mssvm03 UR - https://global-sci.org/intro/article_detail/nmtma/5894.html KW - Euler's elastica, augmented Lagrangian method, image denoising, image inpainting, image zooming. AB -

In this paper, a fast algorithm for Euler's elastica functional is proposed, in which the Euler's elastica functional is reformulated as a constrained minimization problem. Combining the augmented Lagrangian method and operator splitting techniques, the resulting saddle-point problem is solved by a serial of subproblems. To tackle the nonlinear constraints arising in the model, a novel fixed-point-based approach is proposed so that all the subproblems either is a linear problem or has a closed-form solution. We show the good performance of our approach in terms of speed and reliability using numerous numerical examples on synthetic, real-world and medical images for image denoising, image inpainting and image zooming problems.