activity
20182021
most citedTowards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy

52 citations · 61 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20212 cited

Deep Convolutional Sparse Coding Network for Pansharpening with Guidance of Side Information

Shuang Xu, Jiangshe Zhang, Kai Sun +4

Pansharpening is a fundamental issue in remote sensing field. This paper proposes a side information partially guided convolutional sparse coding (SCSC) model for pansharpening. Th…

cs.CV2021

Deep Gradient Projection Networks for Pan-sharpening

Shuang Xu, Jiangshe Zhang, Zixiang Zhao +3

Pan-sharpening is an important technique for remote sensing imaging systems to obtain high resolution multispectral images. Recently, deep learning has become the most popular tool…

cs.CV202052 cited

Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy

Shuang Xu, Lizhen Ji, Zhe Wang +4

Multi-focus image fusion (MFF) is a popular technique to generate an all-in-focus image, where all objects in the scene are sharp. However, existing methods pay little attention to…

cs.CV2020

MFIF-GAN: A New Generative Adversarial Network for Multi-Focus Image Fusion

Yicheng Wang, Shuang Xu, Junmin Liu +3

Multi-Focus Image Fusion (MFIF) is a promising image enhancement technique to obtain all-in-focus images meeting visual needs and it is a precondition of other computer vision task…

eess.IV20207 cited

Deep Convolutional Sparse Coding Networks for Image Fusion

Shuang Xu, Zixiang Zhao, Yicheng Wang +3

Image fusion is a significant problem in many fields including digital photography, computational imaging and remote sensing, to name but a few. Recently, deep learning has emerged…

stat.ML2019

Adaptive Quantile Low-Rank Matrix Factorization

Shuang Xu, Chun-Xia Zhang, Jiangshe Zhang

Low-rank matrix factorization (LRMF) has received much popularity owing to its successful applications in both computer vision and data mining. By assuming noise to come from a Gau…