328 citations · 657 across the 15 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
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…