Academic Homepage

Xuheng Cao 曹栩珩

Computational Imaging · Hyperspectral Imaging · Measurement Science

My research connects imaging physics, inverse reconstruction, and precision measurement. I am interested in hyperspectral image fusion, physics-guided learning, computational optics, and SI-traceable infrared thermometry.

Affiliation IPOE, Tongji University

Joint Laboratory National Institute of Metrology, China

Research Computational imaging and hyperspectral reconstruction

Measurement Infrared thermometry and radiometric traceability

Publications GitHub Email

01 · Profile

Research across imaging, algorithms, and measurement.

A compact overview of my academic interests and working approach.

About

I work on computational imaging problems in which the observation model, reconstruction algorithm, and measurement process must remain physically consistent. My current interests span hyperspectral and multispectral image fusion, spectral reconstruction, deep unfolding, computational optics, and infrared temperature measurement.

A recurring goal in my work is to connect algorithmic performance with interpretable physical models and experimentally verifiable quantities, rather than treating sensing and reconstruction as separate stages.

02 · Research

Research directions

Three closely related themes connect optical sensing, inverse reconstruction, and traceable measurement.

Hyperspectral & Computational Imaging

High-resolution hyperspectral reconstruction, HSI–MSI fusion, spectral reconstruction, semi-blind inverse imaging, and computational imaging systems.

Physics-guided Learning

Deep unfolding, model-based neural networks, degradation estimation, inverse problems, and learning methods that retain explicit links to the image formation model.

Infrared Metrology & Thermometry

SI-traceable infrared temperature measurement, blackbody calibration, radiometric transfer, and large-area temperature-field reconstruction.

03 · Publications

Publications

Peer-reviewed work in computational imaging, hyperspectral reconstruction, optics, and measurement science.

11 records

2026

SI-Traceable Infrared Snapshot Thermometry for Full-Field Wafer Temperature Mapping on Electrostatic Chucks

X. Cao, Q. Gao, J. Tao, J. Song, X. Cheng* and X. Hao*

Light: Advanced Manufacturing

Accepted

2026

A Discrete–Continuous MAP Formulation for Kernel-Free Semi-Blind Hyperspectral Computational Imaging

X. Cao, J. Wang, Y. Lian, X. Han, X. Wang, and X. Hao*

iOptics

Paper Code

2025

Cross-domain-aware Deep Unfolding Transformer for Hyperspectral Image Super-resolution

X. Cao, X. Wang, X. Dun, Y. Lian, X. Cheng, and X. Hao*

Pattern Recognition

Paper Code

2025

Large-area Low-temperature Vacuum Blackbody System of High Emissivity and Temperature Uniformity

J. Song^†, X. Cao^†, G. Wang, J. Zhou, R. Sima, C. Xu, and X. Hao*

IEEE Transactions on Instrumentation and Measurement

Paper

2024

Unsupervised Hybrid Network of Transformer and CNN for Blind Hyperspectral and Multispectral Image Fusion Highly Cited

X. Cao, Y. Lian*, K. Wang, C. Ma, and X. Xu

IEEE Transactions on Geoscience and Remote Sensing

Paper Code

2024

Unsupervised Spectral Reconstruction from RGB Images under Two Lighting Conditions

X. Cao, Y. Lian*, J. Li, Z. Liu, and K. Wang

Optics Letters

Paper Code

2024

Unsupervised Multi-level Spatio-spectral Fusion Transformer for Hyperspectral Image Super-resolution

X. Cao, Y. Lian*, J. Li, K. Wang, and C. Ma

Optics & Laser Technology

Paper Code

2023

Hyperspectral Image Super-resolution via Spectral Matching and Correction

X. Cao, Y. Lian*, Z. Liu, J. Wu, W. Zhang, and J. Liu

Journal of the Optical Society of America A

Paper

2023

Universal High Spatial Resolution Hyperspectral Imaging using Hybrid-resolution Image Fusion

X. Cao, Y. Lian*, Z. Liu, H. Zhou, B. Wang, B. Huang, and W. Zhang

Optical Engineering

Paper Code

2022

Hyperspectral Image Super-resolution via a Multi-stage Scheme without Employing Spatial Degradation

X. Cao, Y. Lian*, Z. Liu, H. Zhou, B. Wang, W. Zhang, and B. Huang

Optics Letters

Paper Code

2022

Hyperspectral Image Super-resolution based on the Transfer of Both Spectra and Multi-level Features

X. Cao, Y. Lian*, Z. Liu, H. Zhou, X. Hu, B. Huang, and W. Zhang

Optics Letters

Paper

04 · Software

Open-source software

Research code and reusable software developed alongside my work.

Python package

Imgvision

Open-source image-processing package with public release and download statistics.

Python package

paddleiv

Open-source research software with public release and download statistics.

05 · Service

Academic service

Peer-review service across imaging, vision, optics, remote sensing, and intelligent systems.

Reviewing

Optica IEEE GRSM IEEE PAMI ISPRS Journal of Photogrammetry and Remote Sensing IEEE TIP IEEE TII IEEE TCSVT IEEE TCYB International Journal of Computer Vision Information Fusion

06 · Contact

Research discussion and collaboration

For research, software, and publication correspondence, please contact me by email.

caoxuheng@tongji.edu.cn caoxuhengcn@gmail.com GitHub