7 papers
Spectral Compressive Imaging via Chromaticity-Intensity Decomposition
Xiaodong Wang, Zijun He, Ping Wang +3
In coded aperture snapshot spectral imaging (CASSI), the captured measurement entangles spatial and spectral information, posing a severely ill-posed inverse problem for hyperspect…
Progressive Flow-inspired Unfolding for Spectral Compressive Imaging
Xiaodong Wang, Ping Wang, Zijun He +2
Coded aperture snapshot spectral imaging (CASSI) retrieves a 3D hyperspectral image (HSI) from a single 2D compressed measurement, which is a highly challenging reconstruction task…
Plug-and-play Diffusion Models for Image Compressive Sensing with Data Consistency Projection
Xiaodong Wang, Ping Wang, Zhangyuan Li +1
We explore the connection between Plug-and-Play (PnP) methods and Denoising Diffusion Implicit Models (DDIM) for solving ill-posed inverse problems, with a focus on single-pixel im…
Texture-aware Intrinsic Image Decomposition with Model- and Learning-based Priors
Xiaodong Wang, Zijun He, Xin Yuan
This paper aims to recover the intrinsic reflectance layer and shading layer given a single image. Though this intrinsic image decomposition problem has been studied for decades, i…
Unfolding Framework with Complex-Valued Deformable Attention for High-Quality Computer-Generated Hologram Generation
Haomiao Zhang, Zhangyuan Li, Yanling Piao +6
Computer-generated holography (CGH) has gained wide attention with deep learning-based algorithms. However, due to its nonlinear and ill-posed nature, challenges remain in achievin…
Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging
Ping Wang, Lishun Wang, Gang Qu +3
Deep-unrolling and plug-and-play (PnP) approaches have become the de-facto standard solvers for single-pixel imaging (SPI) inverse problem. PnP approaches, a class of iterative alg…