activity
20182026
most citedSpatial-Spectral Fusion by Combining Deep Learning and Variation Model

83 citations · 177 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Global-Scale Self-Supervised Spatiotemporal Learning for NDVI Time-Series Reconstruction

Ang Li, Menghui Jiang, Xiaobin Guan +2

Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning provides a promising solution…

physics.ao-ph2026

30-meter Land Surface Temperature from Landsat via Progressive Self-Training Downscaling

Huanfeng Shen, Chan Li, Menghui Jiang +3

Land surface temperature (LST) is a critical parameter for characterizing surface energy balance and hydrothermal processes. While Landsat provides invaluable LST observations at m…

physics.ao-ph2025

A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval

Tian Xie, Menghui Jiang, Chao Zeng +4

Land surface temperature (LST) is a fundamental physical variable in land-atmosphere interactions, surface energy budgets, and climate processes. LST derived from medium- to high-r…

physics.ao-ph2025★ 2 cited

A Mechanism-Learning Deeply Coupled Model for Remote Sensing Retrieval of Global Land Surface Temperature

Tian Xie, Menghui Jiang, Huanfeng Shen +5

Land surface temperature (LST) retrieval from remote sensing data is pivotal for analyzing climate processes and surface energy budgets. However, LST retrieval is an ill-posed inve…

physics.ao-ph2023

A physics-constrained machine learning method for mapping gapless land surface temperature

Jun Ma, Huanfeng Shen, Menghui Jiang +5

More accurate, spatio-temporally, and physically consistent LST estimation has been a main interest in Earth system research. Developing physics-driven mechanism models and data-dr…

eess.IV2021★ 27 cited

An Integrated Framework for the Heterogeneous Spatio-Spectral-Temporal Fusion of Remote Sensing Images

Menghui Jiang, Huanfeng Shen, Jie Li +1

Image fusion technology is widely used to fuse the complementary information between multi-source remote sensing images. Inspired by the frontier of deep learning, this paper first…

eess.IV2021★ 65 cited

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion

Huanfeng Shen, Menghui Jiang, Jie Li +3

In the fields of image restoration and image fusion, model-driven methods and data-driven methods are the two representative frameworks. However, both approaches have their respect…

cs.CV2018★ 83 cited

Spatial-Spectral Fusion by Combining Deep Learning and Variation Model

Huanfeng Shen, Menghui Jiang, Jie Li +3

In the field of spatial-spectral fusion, the model-based method and the deep learning (DL)-based method are state-of-the-art. This paper presents a fusion method that incorporates…