Author

Chunlin Wu

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Preprint Aug 2026

A Globally Convergent Algorithm for Total Scaled-Gradient Variation via Cone-Constrained Bilinear Decomposition

The proposed reformulation of the total scaled-gradient variation regularizer achieves PSNR and SSIM competitive with or superior to representative variational methods, especially at high noise levels, and improves the structural reconstruction under dense and sparse scanning.

Hai-Bin Su, Chunlin Wu, Huibin Chang et al. · 0 citations

Preprint Aug 2026

A Cone-Constrained Bilinear Decomposition for Total Scaled-Gradient Variation Models

The total scaled-gradient variation (TSGV) regularizer, derived from sparse modeling of piecewise-linear structures, has been shown to preserve edges and corners in image restoration. However, its highly nonconvex and nonlinear nature poses severe computational challenges, as existing methods often suffer from paramete...

Hai-Bin Su, Chunlin Wu, Huibin Chang et al. · 0 citations

Open access Jul 2026

Learned spherical ADMM for Rician MRI denoising

This paper proposes a novel learned spherical alternating direction method of multipliers (LSADMMs) for effective Rician noise removal under spherical constraints, and incorporates a noise-level estimation prefix that provides adaptive guidance across noise levels.

Jun Shi, Zhifang Liu, Chunlin Wu et al. · Inverse Problems · 0 citations