52 citations · 106 across the 9 of their papers we have counts for
6 papers · 1 filter
DDFM: Denoising Diffusion Model for Multi-Modality Image Fusion
Zixiang Zhao, Haowen Bai, Yuanzhi Zhu +7
Multi-modality image fusion aims to combine different modalities to produce fused images that retain the complementary features of each modality, such as functional highlights and…
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…