10 papers
Foundation Models in Remote Sensing: Evolving from Unimodality to Multimodality
Danfeng Hong, Chenyu Li, Xuyang Li +2
Remote sensing (RS) techniques are increasingly crucial for deepening our understanding of the planet. As the volume and diversity of RS data continue to grow exponentially, there…
Hyperspectral Imaging
Danfeng Hong, Chenyu Li, Naoto Yokoya +6
Hyperspectral imaging (HSI) is an advanced sensing modality that simultaneously captures spatial and spectral information, enabling non-invasive, label-free analysis of material, c…
KANO: Kolmogorov-Arnold Neural Operator for Image Super-Resolution
Chenyu Li, Danfeng Hong, Bing Zhang +2
The highly nonlinear degradation process, complex physical interactions, and various sources of uncertainty render single-image Super-resolution (SR) a particularly challenging tas…
Any-Optical-Model: A Universal Foundation Model for Optical Remote Sensing
Xuyang Li, Chenyu Li, Danfeng Hong
Optical satellites, with their diverse band layouts and ground sampling distances, supply indispensable evidence for tasks ranging from ecosystem surveillance to emergency response…
MambaX: Image Super-Resolution with State Predictive Control
Chenyu Li, Danfeng Hong, Bing Zhang +3
Image super-resolution (SR) is a critical technology for overcoming the inherent hardware limitations of sensors. However, existing approaches mainly focus on directly enhancing th…
Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt
Jie Deng, Danfeng Hong, Chenyu Li +1
We propose a novel joint framework by integrating super-resolution and segmentation, called JointSeg, which enables the generation of 1-meter ISA maps directly from freely availabl…