We consider an inexact version of the popular Fast Iterative Soft-Thresholding Algorithm (FISTA) suited for minimizing the sum of a differentiable convex data fidelity function plus a nondifferentiable convex regularizer whose proximal operator is not computable in closed form. The proposed method is a nested primal–dual forward–backward method inspired by the methodology developed in [10], according to which the proximal-gradient point is approximated by means of a prefixed number of inner primal-dual iterates initialized with an appropriate warmstart strategy. We report some preliminary numerical results on a weighted least squares total-variation based model for Poisson image deblurring, which show the efficiency of the proposed FISTA-like method with respect to other strategies for defining the inner loop associated to the proximal step.

A comparison of nested primal-dual forward-backward methods for Poisson image deblurring / Rebegoldi, Simone; Bonettini, Silvia; Prato, Marco. - (2021), pp. 87-92. ((Intervento presentato al convegno 21st International Conference on Computational Science and Its Applications, ICCSA 2021 tenutosi a Cagliari nel 13-16 settembre 2021 [10.1109/ICCSA54496.2021.00022].

A comparison of nested primal-dual forward-backward methods for Poisson image deblurring

Bonettini, Silvia;Prato, Marco
2021

Abstract

We consider an inexact version of the popular Fast Iterative Soft-Thresholding Algorithm (FISTA) suited for minimizing the sum of a differentiable convex data fidelity function plus a nondifferentiable convex regularizer whose proximal operator is not computable in closed form. The proposed method is a nested primal–dual forward–backward method inspired by the methodology developed in [10], according to which the proximal-gradient point is approximated by means of a prefixed number of inner primal-dual iterates initialized with an appropriate warmstart strategy. We report some preliminary numerical results on a weighted least squares total-variation based model for Poisson image deblurring, which show the efficiency of the proposed FISTA-like method with respect to other strategies for defining the inner loop associated to the proximal step.
21st International Conference on Computational Science and Its Applications, ICCSA 2021
Cagliari
13-16 settembre 2021
87
92
Rebegoldi, Simone; Bonettini, Silvia; Prato, Marco
A comparison of nested primal-dual forward-backward methods for Poisson image deblurring / Rebegoldi, Simone; Bonettini, Silvia; Prato, Marco. - (2021), pp. 87-92. ((Intervento presentato al convegno 21st International Conference on Computational Science and Its Applications, ICCSA 2021 tenutosi a Cagliari nel 13-16 settembre 2021 [10.1109/ICCSA54496.2021.00022].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1273477
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