A primal-dual gradient method for image decomposition based on (BV, H−1)

The main aim of this paper is to accelerate the image decomposition model based on (BV, H−1). It is solved with a particularly effective primal-dual gradient descent algorithm. The algorithm works on the primal-dual formulation and exploits the information of the primal and dual variables simultaneously. It converges significantly faster than some popular existing methods in numerical experiments. This approach is to some extent related to projection type methods for solving variational inequalities.

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