Overview: The Split Bregman method is a technique for solving a variety of L1-regularized optimization problems, and is particularly effective for problems involving total-variation regularization. Split Bregman is one of the fastest solvers for Total-Variation denoising, image reconstruction from Fourier coefficients, convex image segmentation, and many other problems. The method is a re-interpretation of the alternating direction method of multipliers that is specially adapted to L1 problems.A complete technical explanation of the Split Bregman method can be found in the paper The Split Bregman Method for L1 Regularized Problems, by Tom Goldstein and Stanley Osher.
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