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A first-order primal-dual algorithm for convex problems with applications to imaging

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Figure

Figure 1: The figure shows the sequence (γτ n ) n ≥ 1 , using γ = 1. Observe that it goes very fast to 1/n, in a way which is quite insensitive to the initial τ 0
Figure 2: Image denoising using the ROF model. The left column shows the noisy input image of size 256 × 256, with additive zero mean Gaussian noise (σ = 0.05) and the denoised image using λ = 16
Table 1: Performance evaluation using the images shown in Figure 2. The entries in the table refer to the number of iterations respectively the CPU times in seconds the algorithms needed to drop the root mean squared error of the solution below the error t
Figure 3: Convergence of AHZC and ALG2 for the experiment in the last column of Table 1
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