A Second-Order Image Denoising Model for Contrast Preservation

doi:10.1007/s42967-023-00344-z

Abstract

Abstract: In this work, we propose a second-order model for image denoising by employing a novel potential function recently developed in Zhu (J Sci Comput 88: 46, 2021) for the design of a regularization term. Due to this new second-order derivative based regularizer, the model is able to alleviate the staircase effect and preserve image contrast. The augmented Lagrangian method (ALM) is utilized to minimize the associated functional and convergence analysis is established for the proposed algorithm. Numerical experiments are presented to demonstrate the features of the proposed model.

Key words: Image denoising, Variational model, Image contrast, Augmented Lagrangian method (ALM)

Wei Zhu. A Second-Order Image Denoising Model for Contrast Preservation[J]. Communications on Applied Mathematics and Computation, 2024, 6(2): 1406-1427.

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