1. Zero norm based analysis model for image smoothing and reconstruction
- Author
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Jia Li, Zhengan Yao, Jiebo Song, Chenglong Bao, and Kaisheng Ma
- Subjects
Applied Mathematics ,Signal Processing ,Zero norm ,Algorithm ,Mathematical Physics ,Smoothing ,Computer Science Applications ,Theoretical Computer Science ,Image (mathematics) ,Mathematics - Abstract
The sparsity-based approaches have demonstrated promising performance in image processing. In this paper, for better preservation of the salient edge structures of images, we propose an ℓ 0 + ℓ 2-norm based analysis model, which requires solving a challenging non-separable ℓ 0-norm related minimization problem, and we also propose an inexact augmented Lagrangian method with proven convergence to a local minimum. Extensive experiments in image smoothing, including texture removal and context smoothing, show that our method achieves better visual results over various sparsity-based models and the CNN method. Also, experiments on sparse view CT reconstruction further validate the advantage of the proposed method.
- Published
- 2020
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