Restoration of Poissonian Images Using Nonconvex Regularizer with Overlapping Group Sparsity

Liu, Xinwu; Lian, Wenhui

doi:10.15388/22-INFOR480

Informatica

Restoration of Poissonian Images Using Nonconvex Regularizer with Overlapping Group Sparsity

Volume 33, Issue 3 (2022), pp. 573–592

Xinwu Liu Wenhui Lian

https://doi.org/10.15388/22-INFOR480

Pub. online: 24 March 2022 Type: Research Article

Open Access

Received
1 April 2021

Accepted
1 March 2022

Published
24 March 2022

Abstract

Aimed at achieving the accurate restoration of Poissonian images that exhibit neat edges and no staircase effect, this article develops a novel hybrid nonconvex double regularizer model. The proposed scheme closely takes the advantages of total variation with overlapping group sparsity and nonconvex high-order total variation priors. The overlapping group sparsity is adopted to globally suppress the staircase artifacts, while the nonconvex high-order regularization plays the role of locally preserving the significant image features and edge details. Computationally, a quite efficient alternating direction method of multipliers, associated with the iteratively reweighted ${\ell _{1}}$ algorithm and the majorization-minimization method, is employed to settle the optimization problem iteratively. Finally, exhaustive simulation experiments are executed for recovering Poissonian images, which are made comparisons with several state-of-the-art restoration strategies, indicate the brilliant performance of our model in terms of intuitive effects and accuracy evaluation.

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Keywords

image restoration Poisson noise nonconvex regularizer overlapping group sparsity alternating direction method of multipliers

Funding

This work was supported by Hunan Provincial Natural Science Foundation of China (2020JJ4285) and Scientific Research Fund of Hunan Provincial Education Department (19B215).

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