7 papers
Beyond Low-rankness: Guaranteed Matrix Recovery via Modified Nuclear Norm
Jiangjun Peng, Yisi Luo, Xiangyong Cao +2
The nuclear norm (NN) has been widely explored in matrix recovery problems, such as Robust PCA and matrix completion, leveraging the inherent global low-rank structure of the data.…
Task-driven Image Fusion with Learnable Fusion Loss
Haowen Bai, Jiangshe Zhang, Zixiang Zhao +5
Multi-modal image fusion aggregates information from multiple sensor sources, achieving superior visual quality and perceptual features compared to single-source images, often impr…
Deep Unfolding Multi-modal Image Fusion Network via Attribution Analysis
Haowen Bai, Zixiang Zhao, Jiangshe Zhang +5
Multi-modal image fusion synthesizes information from multiple sources into a single image, facilitating downstream tasks such as semantic segmentation. Current approaches primaril…
Haar Nuclear Norms with Applications to Remote Sensing Imagery Restoration
Shuang Xu, Chang Yu, Jiangjun Peng +2
Remote sensing image restoration aims to reconstruct missing or corrupted areas within images. To date, low-rank based models have garnered significant interest in this field. This…
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image
Shuang Xu, Zixiang Zhao, Haowen Bai +4
Hyperspectral images (HSIs) are frequently noisy and of low resolution due to the constraints of imaging devices. Recently launched satellites can concurrently acquire HSIs and pan…
HSIGene: A Foundation Model For Hyperspectral Image Generation
Li Pang, Xiangyong Cao, Datao Tang +4
Hyperspectral image (HSI) plays a vital role in various fields such as agriculture and environmental monitoring. However, due to the expensive acquisition cost, the number of hyper…