An efficient semismooth* Newton method is presented for minimizing Tikhonov functionals with total variation regularization, offering superlinear convergence for large-scale tomographic imaging problems.
SSSN” stands for our semismooth ∗ Newton approach, i.e., Algorithm 3.3, and “CP
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Efficient TV regularization of large-scale linear inverse problems via the SCD semismooth* Newton method with applications in tomography
An efficient semismooth* Newton method is presented for minimizing Tikhonov functionals with total variation regularization, offering superlinear convergence for large-scale tomographic imaging problems.