328 citations · 657 across the 15 of their papers we have counts for
16 papers
CGFformer: Cluster-Guidance Frequency Transformer for Pansharpening
Zijian Zhou, Jianing Zhang, Kai Sun +3
Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) images with high-resolution panchromatic (PAN) images. Howe…
Seismic Data Interpolation via Denoising Diffusion Implicit Models with Coherence-corrected Resampling
Xiaoli Wei, Chunxia Zhang, Hongtao Wang +5
Accurate interpolation of seismic data is crucial for improving the quality of imaging and interpretation. In recent years, deep learning models such as U-Net and generative advers…
UPNet: Uncertainty-based Picking Deep Learning Network for Robust First Break Picking
Hongtao Wang, Jiangshe Zhang, Xiaoli Wei +2
In seismic exploration, first break (FB) picking is a crucial aspect in the determination of subsurface velocity models, significantly influencing the placement of wells. Many deep…
MSSPN: Automatic First Arrival Picking using Multi-Stage Segmentation Picking Network
Hongtao Wang, Jiangshe Zhang, Xiaoli Wei +4
Picking the first arrival times of prestack gathers is called First Arrival Time (FAT) picking, which is an indispensable step in seismic data processing, and is mainly solved manu…
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…
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…
FGF-GAN: A Lightweight Generative Adversarial Network for Pansharpening via Fast Guided Filter
Zixiang Zhao, Jiangshe Zhang, Shuang Xu +4
Pansharpening is a widely used image enhancement technique for remote sensing. Its principle is to fuse the input high-resolution single-channel panchromatic (PAN) image and low-re…
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…
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…
When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method
Zixiang Zhao, Jiangshe Zhang, Shuang Xu +3
Infrared and visible image fusion, as a hot topic in image processing and image enhancement, aims to produce fused images retaining the detail texture information in visible images…
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…
Bayesian Fusion for Infrared and Visible Images
Zixiang Zhao, Shuang Xu, Chunxia Zhang +2
Infrared and visible image fusion has been a hot issue in image fusion. In this task, a fused image containing both the gradient and detailed texture information of visible images…
Efficient and Model-Based Infrared and Visible Image Fusion Via Algorithm Unrolling
Zixiang Zhao, Shuang Xu, Jiangshe Zhang +3
Infrared and visible image fusion (IVIF) expects to obtain images that retain thermal radiation information from infrared images and texture details from visible images. In this pa…
DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion
Zixiang Zhao, Shuang Xu, Chunxia Zhang +3
Infrared and visible image fusion, a hot topic in the field of image processing, aims at obtaining fused images keeping the advantages of source images. This paper proposes a novel…
MFFW: A new dataset for multi-focus image fusion
Shuang Xu, Xiaoli Wei, Chunxia Zhang +2
Multi-focus image fusion (MFF) is a fundamental task in the field of computational photography. Current methods have achieved significant performance improvement. It is found that…
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…