Chao Qu's homepage

Chao Qu

PhD Candidate

The 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.

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Interests

Infrared Imaging
Computational imaging
Neuromorphic 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

Noise Modeling

Physics-guided infrared spatiotemporal noise modeling based on hybrid neural representation

We propose an infrared spatiotemporal noise modeling framework (IRSTN) based on hybrid neural representation, which leverages unpaired video data to simulate real-world noise.

Oct 23, 2024

Destriping

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

We propose a self-supervised image denoising and destriping method based on blind-spot regularization, named Self-BSR, which transforms the overall denoising and destriping problem into a modeling task for two spatially correlated signals, image and stripe.

Sep 9, 2024

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 (2024). XXXXXX. CVPR 2025 [Submitted].

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

Chao Qu (2024). Self-BSR: Self-supervised Image Denoising and Destriping Based on Blind-Spot Regularization. IEEE Transactions on Circuits and Systems for Video Technology [Minor Revision].

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

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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.