Author

Hai-Bin Su

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Preprint Oct 2026

Gauss-Map Variation for Image Denoising: Geometric Analysis and an Anderson--Accelerated Majorization--Minimization Method

We propose a Gauss-map variation (GMV) model for image denoising that measures the spatial variation of the tangent-plane projectors of the scaled image graph. We establish an equivalent representation of the regularizer in terms of the corresponding Gauss map and, using differential geometric tools including tubular c...

Hai-Bin Su · 0 citations

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