79 citations · 161 across the 8 of their papers we have counts for
8 papers
Unrolling Plug-and-Play Network for Hyperspectral Unmixing
Min Zhao, Linruize Tang, Jie Chen
Deep learning based unmixing methods have received great attention in recent years and achieve remarkable performance. These methods employ a data-driven approach to extract struct…
AE-RED: A Hyperspectral Unmixing Framework Powered by Deep Autoencoder and Regularization by Denoising
Min Zhao, Jie Chen, Nicolas Dobigeon
Spectral unmixing has been extensively studied with a variety of methods and used in many applications. Recently, data-driven techniques with deep learning methods have obtained gr…
Guided Deep Generative Model-based Spatial Regularization for Multiband Imaging Inverse Problems
Min Zhao, Nicolas Dobigeon, Jie Chen
When adopting a model-based formulation, solving inverse problems encountered in multiband imaging requires to define spatial and spectral regularizations. In most of the works of…
Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing
Jie Chen, Min Zhao, Xiuheng Wang +2
Spectral unmixing is one of the most important quantitative analysis tasks in hyperspectral data processing. Conventional physics-based models are characterized by clear interpreta…
A Plug-and-Play Priors Framework for Hyperspectral Unmixing
Min zhao, Xiuheng Wang, Jie Chen +1
Spectral unmixing is a widely used technique in hyperspectral image processing and analysis. It aims to separate mixed pixels into the component materials and their corresponding a…
Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors
Min Zhao, Tiande Gao, Jie Chen +1
Nowadays, nonnegative matrix factorization (NMF) based methods have been widely applied to blind spectral unmixing. Introducing proper regularizers to NMF is crucial for mathematic…
Hyperspectral Unmixing via Deep Autoencoder Networks for a Generalized Linear-Mixture/Nonlinear-Fluctuation Model
Min Zhao, Mou Wang, Jie Chen +1
Spectral unmixing is an important task in hyperspectral image processing for separating the mixed spectral data pertaining to various materials observed individual pixels. Recently…
A laboratory-created dataset with ground-truth for hyperspectral unmixing evaluation
Min Zhao, Jie Chen, Zhe He
Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been p…