A Fast Augmented Lagrangian Method for Euler’s Elastica Model
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 sub-problems. To tackle the nonlinear constraints arising in the model, a novel fixed-point-based approach is proposed so that all the sub-problems either are linear problems or have closed form solutions. Numerical examples are provided to demonstrate the performance of the proposed method.
KeywordsClosed Form Solution Image Denoising Augmented Lagrangian Method Constrain Minimization Problem Augmented Lagrangian Algorithm
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