Papers
1
Total Citations
19
H-Index
1
About
Pan Mu is a rising figure in computer vision, specializing in underwater image enhancement and restoration. Her key research areas include image processing, deep learning-based enhancement models, and structure-aware computational imaging. Her most notable contribution is the development of a "Structure-Inferred Bi-level Model for Underwater Image Enhancement" (2022), which addresses the persistent challenges of color cast and low visibility in underwater imagery caused by light scattering and absorption. This work, already garnering 19 citations, introduces a novel approach that leverages structural inference to improve image clarity and color fidelity, directly benefiting applications in underwater robotics and marine exploration. Mu's research stands out for its practical impact, offering robust solutions for real-world underwater environments. Her achievements reflect a growing influence in the field, with her work cited as a key reference for advancing autonomous underwater systems. As a young researcher, Pan Mu is poised to make further contributions to visual computing in challenging aquatic conditions.
Research Focus
Key Achievements
Top Papers
- 1Structure-Inferred Bi-level Model for Underwater Image Enhancement19 citations · 2022