期刊
NUMERICAL MATHEMATICS-THEORY METHODS AND APPLICATIONS
卷 6, 期 1, 页码 47-71出版社
GLOBAL SCIENCE PRESS
DOI: 10.4208/nmtma.2013.mssvm03
关键词
Euler's elastica; augmented Lagrangian method; image denoising; image inpainting; image zooming
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.
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