28 citations · 57 across the 11 of their papers we have counts for
11 papers
A Globally Convergent Algorithm for Total Scaled-Gradient Variation via Cone-Constrained Bilinear Decomposition
Haibin Su, Chunlin Wu, Huibin Chang +1
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 restorati…
On anisotropic non-Lipschitz restoration model: lower bound theory and convergent algorithm
Chunlin Wu, Xuan Lin, Yufei Zhao
For nonconvex and nonsmooth restoration models, the lower bound theory reveals their good edge recovery ability, and related analysis can help to design convergent algorithms. Exis…
A fast method for simultaneous reconstruction and segmentation in X-ray CT application
Yiqiu Dong, Chunlin Wu, Shi Yan
In this paper, we propose a fast method for simultaneous reconstruction and segmentation (SRS) in X-ray computed tomography (CT). Our work is based on the SRS model where Bayes' ru…
Effective two-stage image segmentation: a new non-Lipschitz decomposition approach with convergent algorithm
Xueyan Guo, Yunhua Xue, Chunlin Wu
Image segmentation is an important median level vision topic. Accurate and efficient multiphase segmentation for images with intensity inhomogeneity is still a great challenge. We…
Every critical point of an L0 composite minimization problem is a local minimizer
Xue Feng, Chunlin Wu
Nowadays, L0 optimization model has shown its superiority when pursuing sparsity in many areas. For this nonconvex problem, most of the algorithms can only converge to one of its c…
An Efficient and Globally Convergent Algorithm for - Model in Group Sparse Optimization
Yunhua Xue, Yanfei Feng, Chunlin Wu
Group sparsity combines the underlying sparsity and group structure of the data in problems. We develop a proximally linearized algorithm InISSAPL for the non-Lipschitz group spars…
An iterative support shrinking algorithm for - minimization
Zhifang Liu, Yanan Zhao, Chunlin Wu
We present an iterative support shrinking algorithm for - minimization~(). This algorithm guarantees the nonexpensiveness of the sign…
Triangulated Surface Denoising using High Order Regularization with Dynamic Weights
Zheng Liu, Rongjie Lai, Huayan Zhang +1
Recovering high quality surfaces from noisy triangulated surfaces is a fundamental important problem in geometry processing. Sharp features including edges and corners can not be w…
-regularized Variational Methods for Sparse Phase Retrieval
Yuping Duan, Chunlin Wu, Zhi-Feng Pang +1
We study the problem of recovering the underlining sparse signals from clean or noisy phaseless measurements. Due to the sparse prior of signals, we adopt an L0regularized variatio…
A General Truncated Regularization Framework for Contrast-Preserving Variational Signal and Image Restoration: Motivation and Implementation
Chunlin Wu, Zhifang Liu, Shuang Wen
Variational methods have become an important kind of methods in signal and image restoration - a typical inverse problem. One important minimization model consists of the squared $…
The Continuity of Images by Transmission Imaging Revisited
Zhitao Fan, Feng Guan, Chunlin Wu +1
Transmission imaging, as an important imaging technique widely used in astronomy, medical diagnosis, and biology science, has been shown in [49] quite different from reflection ima…