Chao Qu's homepage

Chao Qu

PhD Candidate

Nanjing University of Science and Technology (NJUST)

Biography

I received the B.E degree in Electronic Science and Technology from the Nanjing University of Science and Technology in 2019. I am currently pursuing the Ph.D. degree with the School of Electronic and Optical Engineering. My current research interests include infrared imaging, computational imaging and neuromorphic imaging.

Interests

Infrared Imaging
Neuromorphic Imaging
Computational imaging

Education

MEng & PhD in Optical Engineering, 2020-Present
Nanjing University of Science and Technology
BEng in Electronic Science and Technology, 2015-2019
Nanjing University of Science and Technology

Featured Publications

Destriping

Self-BSR: Self-supervised Image Denoising and Destriping Based on Blind-Spot Regularization

We propose Self-BSR, a self-supervised image denoising and destriping method based on blind-spot regularization. This approach reformulates the overall denoising and destriping problem as a modeling task involving two spatially correlated signals: the image and the stripe.

Apr 9, 2025

Infrared Degradation Modeling

Frequency-Aware Degradation Modeling for Real-World Thermal Image Super-Resolution

To enhance the SR performance for real-world thermal images, we propose an unsupervised SR framework that integrates degradation modeling with corresponding SR reconstruction.

Jan 16, 2024

Recent Manuscripts

Chao Qu, Shuo Zhu, Yuhang Wang, Zongze Wu, Xiaoyu Chen, Edmund Y. Lam, Jing Han (2025). Near-Infrared Image Deblurring and Event Denoising with Synergistic Neuromorphic Imaging. arXiv.

PDF DOI

Chao Qu, Zewei Chen, Jingyuan Zhang, Xiaoyu Chen, Jing Han (2025). Self-BSR: Self-supervised Image Denoising and Destriping Based on Blind-Spot Regularization. TCSVT.

PDF Cite Code DOI

Chao Qu (2024). Physics-guided infrared spatiotemporal noise modeling based on hybrid neural representation. IEEE Sensors Journal [Under Review].

Chao Qu, Xiaoyu Chen, Qihan Xu, Jing Han (2024). Frequency-Aware Degradation Modeling for Real-World Thermal Image Super-Resolution. Entropy.

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Projects

The project I participated in as a core member involves infrared characteristic modeling, infrared enhancement, multi-modal fusion, and object detection.