Dr. Xiaohang Zhao, Changchun Institute of Optics, Fine Mechanics and Physics, China
Xiaohang Zhao is a dedicated Ph.D. candidate in Mechatronic Engineering at the University of Chinese Academy of Sciences (UCAS), affiliated with the esteemed Changchun Institute of Optics, Fine Mechanics and Physics. His research emphasizes cutting-edge infrared imaging and remote sensing technologies, particularly for spaceborne applications. Zhao has demonstrated his scientific innovation through multiple first-author publications in high-impact SCI-indexed journals and the successful filing of four patents. His work addresses critical challenges in image quality, including low-light enhancement, stripe noise removal, and blind deblurring. In addition to his academic research, Zhao has contributed to major national defense projects such as the DXX infrared grating camera and the Geological-1 satellite imaging system. With strong expertise in algorithm development, FPGA hardware design, and detector-driven imaging techniques, he actively explores real-time enhancement solutions in space-based imaging. Zhao combines theoretical rigor with practical engineering, aiming to advance China’s capabilities in aerospace and remote sensing.
Publication Profile
orcid
🎓 Education
Xiaohang Zhao earned his Bachelor of Science degree in Electronic Information Science and Technology from Northeast Normal University, where he gained a strong foundation in signal processing, circuit design, and embedded systems. Following his undergraduate studies, he was admitted to the University of Chinese Academy of Sciences (UCAS) for doctoral research in Mechatronic Engineering, joining the prestigious Changchun Institute of Optics, Fine Mechanics and Physics. At UCAS, Zhao has been engaged in advanced courses and research in optical engineering, infrared imaging, sensor data processing, and mechatronic system design. His academic training includes deep exploration of atmospheric scattering models, hardware-software co-design, and scientific programming for large-scale image processing. Under expert supervision, Zhao continues to sharpen his knowledge through national defense-oriented projects and interdisciplinary collaborations, setting a strong foundation for a future in cutting-edge imaging technology, especially focused on spaceborne and defense-related optical systems.
💼 Experience
Xiaohang Zhao is currently a Ph.D. researcher at the Changchun Institute of Optics, Fine Mechanics and Physics, part of the Chinese Academy of Sciences. His professional work spans both algorithm design and hardware implementation for remote sensing applications. He has developed and implemented advanced image processing techniques—including low-light image enhancement, blind deblurring, and stripe noise removal—for real-time space-based imaging systems. Zhao’s experience includes active involvement in defense and aerospace projects such as the DXX infrared grating camera and the Geological-1 satellite imaging mission. He has also contributed to real-world imaging system development using FPGA platforms, ensuring high-efficiency hardware acceleration. His engineering approach combines deep algorithmic insight with system-level design, detector calibration, and embedded optimization. Zhao has collaborated with multidisciplinary teams, integrating sensor data with advanced image enhancement pipelines and ensuring compliance with strict aerospace-grade performance and reliability standards.
🏆 Honors and Awards
Xiaohang Zhao has been recognized for his outstanding research contributions in infrared and remote sensing imaging with several accolades. His innovative work has led to 4 authorized patents in the field of image enhancement and spaceborne imaging algorithms. He is the first author of 5 SCI-indexed journal articles, including publications in high-impact platforms such as IEEE Sensors Journal and Remote Sensing. His academic excellence earned him multiple research scholarships and commendations from the University of Chinese Academy of Sciences. Zhao has also been selected for participation in key national defense projects, highlighting the practical relevance and strategic importance of his research. His commitment to bridging theoretical development with real-world applications has been recognized through internal awards from the Changchun Institute of Optics for innovation in imaging system design and deployment. These honors underscore his growing reputation in the field of high-performance imaging and optical engineering.
🔬 Research Focus
Xiaohang Zhao’s research centers on infrared and remote sensing image enhancement, with a particular focus on spaceborne systems. His work addresses fundamental challenges in low-light image enhancement, blind deblurring, stripe noise removal, and non-uniform illumination compensation, essential for high-precision satellite and defense imaging. He specializes in image quality enhancement algorithms that are tightly coupled with detector characteristics, enabling real-time implementation through FPGA-based hardware acceleration. Zhao also develops atmospheric scattering models to refine image clarity under complex environmental conditions. His technical portfolio includes detector-driven algorithm optimization, real-time enhancement, and noise-resilient imaging techniques suitable for remote and harsh space environments. Zhao’s applied research contributes directly to national defense projects, including the DXX infrared grating camera and Geological-1 satellite imaging, positioning him as a critical contributor to China’s aerospace imaging capabilities. His future goals include advancing autonomous onboard image correction systems for next-generation satellites.
📚 Publications
-
📄 Low-Light Image Enhancement Based on Retinex and Adaptive Histogram Equalization for Spaceborne Systems
-
📄 Stripe Noise Removal in Infrared Images via Dual-Domain Sparse Coding
-
📄 Blind Image Deblurring for Remote Sensing Using Deep Prior and Motion Estimation
-
📄 Real-Time FPGA Implementation of Image Enhancement Algorithms for Onboard Satellite Processing
-
📄 Infrared Image Restoration under Atmospheric Scattering Conditions with Physics-Based Modeling