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Generalized Welsch penalty for edge-aware image decomposition

Edge-aware image decomposition is an essential topic in the field of multimedia signal processing. In this paper, we propose a novel non-convex penalty function, which we name the generalized Welsch function. We show that the proposed penalty function is more than a generalization of most existing p...

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Bibliographic Details
Published in:Multimedia systems 2024-08, Vol.30 (4), Article 186
Main Authors: Yang, Yang, Ji, Shunli, Wang, Xinyu, Zeng, Lanling, Zhan, Yongzhao
Format: Article
Language:English
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Summary:Edge-aware image decomposition is an essential topic in the field of multimedia signal processing. In this paper, we propose a novel non-convex penalty function, which we name the generalized Welsch function. We show that the proposed penalty function is more than a generalization of most existing penalty functions for edge-aware regularization, thus, it better facilitates edge-awareness. We embed the proposed penalty function into a novel optimization model for edge-aware image decomposition. To solve the optimization model with non-convex penalty function, we propose an efficient algorithm based on the additive quadratic minimization and Fourier domain optimization. We have experimented with the proposed method in a variety of tasks, including image smoothing, detail enhancement, HDR tone mapping, and JPEG compression artifact removal. Experiment results show that our method outperforms the state-of-the-art image decomposition methods. Furthermore, our method is highly efficient, it is able to render real-time processing of 720P color images on a modern GPU.
ISSN:0942-4962
1432-1882
DOI:10.1007/s00530-024-01382-0