5 papers
Deep Spectral Prior
Yanqi Cheng, Xuxiang Zhao, Tieyong Zeng +3
We introduce the Deep Spectral Prior (DSP), a new framework for unsupervised image reconstruction that operates entirely in the complex frequency domain. Unlike the Deep Image Prio…
Edge-guided Low-light Image Enhancement with Inertial Bregman Alternating Linearized Minimization
Chaoyan Huang, Zhongming Wu, Tieyong Zeng
Prior-based methods for low-light image enhancement often face challenges in extracting available prior information from dim images. To overcome this limitation, we introduce a sim…
Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems
Chaoyan Huang, Zhongming Wu, Yanqi Cheng +3
Image restoration is typically addressed through non-convex inverse problems, which are often solved using first-order block-wise splitting methods. In this paper, we consider a ge…
Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging
Tsz Ching Chow, Chaoyan Huang, Zhongming Wu +2
Imaging tasks are typically tackled using a structured optimization framework. This paper delves into a class of algorithms for difference-of-convex (DC) structured optimization, f…
Extrapolated Plug-and-Play Three-Operator Splitting Methods for Nonconvex Optimization with Applications to Image Restoration
Zhongming Wu, Chaoyan Huang, Tieyong Zeng
This paper investigates the convergence properties and applications of the three-operator splitting method, also known as Davis-Yin splitting (DYS) method, integrated with extrapol…