18 citations · 62 across the 7 of their papers we have counts for
7 papers
A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing
Yujie Feng, Yin Yang, Xiaohong Fan +3
Recently, deep learning methods have gained remarkable achievements in the field of image restoration for remote sensing (RS). However, most existing RS image restoration methods f…
MVMS-RCN: A Dual-Domain Unfolding CT Reconstruction with Multi-sparse-view and Multi-scale Refinement-correction
Xiaohong Fan, Ke Chen, Huaming Yi +2
X-ray Computed Tomography (CT) is one of the most important diagnostic imaging techniques in clinical applications. Sparse-view CT imaging reduces the number of projection views to…
PRISTA-Net: Deep Iterative Shrinkage Thresholding Network for Coded Diffraction Patterns Phase Retrieval
Aoxu Liu, Xiaohong Fan, Yin Yang +1
The problem of phase retrieval (PR) involves recovering an unknown image from limited amplitude measurement data and is a challenge nonlinear inverse problem in computational imagi…
A Multi-scale Generalized Shrinkage Threshold Network for Image Blind Deblurring in Remote Sensing
Yujie Feng, Yin Yang, Xiaohong Fan +2
Remote sensing images are essential for many applications of the earth's sciences, but their quality can usually be degraded due to limitations in sensor technology and complex ima…
Nest-DGIL: Nesterov-optimized Deep Geometric Incremental Learning for CS Image Reconstruction
Xiaohong Fan, Yin Yang, Ke Chen +2
Proximal gradient-based optimization is one of the most common strategies to solve inverse problem of images, and it is easy to implement. However, these techniques often generate…
An Interpretable MRI Reconstruction Network with Two-grid-cycle Correction and Geometric Prior Distillation
Xiaohong Fan, Yin Yang, Ke Chen +2
Although existing deep learning compressed-sensing-based Magnetic Resonance Imaging (CS-MRI) methods have achieved considerably impressive performance, explainability and generaliz…
Deep Geometric Distillation Network for Compressive Sensing MRI
Xiaohong Fan, Yin Yang, Jianping Zhang
Compressed sensing (CS) is an efficient method to reconstruct MR image from small sampled data in -space and accelerate the acquisition of MRI. In this work, we propose a novel…