Atmospheric Turbulence Mitigation

Latest papers

11 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

TriINR: Unsupervised Atmospheric Turbulence Mitigation with Triple Implicit Neural Representations
Oct 16, 2026Yuka Ogino, Rikuto Otsuka, Yuho Shoji +3Unsupervised Image Restoration Atmospheric Turbulence Mitigation
NEC Corporation, Japan
Deep Learning for Atmospheric Turbulence Mitigation: A Comparison Between GANs and Transformers
Oct 13, 2026Juan S. Carrillo, Jérôme GillesAtmospheric Turbulence Mitigation Image Restoration
San Diego State University, Computational Science Research Center, Department of Mathematics and Statistics, 5500 Campanile Drive, San Diego, CA 92182, USA · San Diego State University, Department of Mathematics and Statistics, 5500 Campanile Drive, San Diego, CA 92182, USA
ASTRA-SR: Atmospheric Seeing and Turbulence Restoration for Astronomical Image Super-Resolution
Sep 22, 2026Xining Ge, Ziteng Cui, Shuhong LiuImage Restoration Image Super-Resolution
Hangzhou Dianzi University · Hong Kong University of Science and Technology, Guangzhou · The University of Tokyo
Restore What Matters: Lessons from Joint Restoration and Recognition
Sep 12, 2026Lanqing Guo, Xijun Wang, Minchul Kim +7Atmospheric Turbulence Mitigation Image Restoration
The University of Texas at Austin, Austin, USA · Purdue University, West Lafayette, USA · Michigan State University, Lansing, USA
Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulence
Jul 1, 2026Abdullah Al Tasim, Wei SunRL Control Aerial Robotics
University of Oklahoma, Norman, Oklahoma, 73019
D $^2$ Turb: Depth-Aware Simulation and Decoupled Learning for Single-Frame Atmospheric Turbulence Mitigation
May 25, 2026Zixiao Hu, Tianyu Li, Guoqing Wang +4Image Deblurring Atmospheric Turbulence Mitigation
University of Electronic Science and Technology of China · Beijing Institute of Space Mechanics and Electricity · School of Physics, Northwest University Xi’an
ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes
May 20, 2026Zhiming Liu, Zhicheng Zou, Nantheera AnantrasirichaiAtmospheric Turbulence Mitigation Video Restoration
Visual Information Laboratory, School of Computer Science, University of Bristol
High-Quality and Efficient Turbulence Mitigation with Events
Mar 21, 2026Xiaoran Zhang, Jian Ding, Yuxing Duan +4Atmospheric Turbulence Mitigation Image Restoration
State Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation, Huazhong University of Science and Technology · School of Computer Science and Engineering, Sun Yat-sen University
High-speed Imaging through Turbulence with Event-based Light Fields
Mar 14, 2026Yu-Hsiang Huang, Levi Burner, Sachin Shah +3Atmospheric Turbulence Mitigation Computational Imaging
University of Maryland, College Park MD 20742, USA · Dartmouth College, Hanover NH 03755, USA
Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis
Mar 2, 2026Junwei Zeng, Dong Liang, Sheng-Jun Huang +2Synthetic Data Augmentation Atmospheric Turbulence Mitigation
Nanjing University of Aeronautics and Astronautics · School of Information Science and Engineering, Lanzhou University
GSTurb: Gaussian Splatting for Atmospheric Turbulence Mitigation
Feb 26, 2026Hanliang Du, Zhangji Lu, Zewei Cai +3Atmospheric Turbulence Mitigation Image Restoration
Faculty of Science and Technology, University of Macau, Macau 999078, China · College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518000, China · College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China +4

Oct 16, 2026J/K move · Enter open · S save

TriINR: Unsupervised Atmospheric Turbulence Mitigation with Triple Implicit Neural Representations

Yuka Ogino, Rikuto Otsuka, Yuho Shoji, Takuya Ogawa+2

NEC Corporation, Japan

Unsupervised Image Restoration Atmospheric Turbulence Mitigation Image Restoration Image Deblurring Implicit Neural Representations Physics-Guided Image Restoration

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Atmospheric turbulence degrades image quality in long-range imaging. The degradation is generally modeled with two spatio-temporally varying components, tilt and blur. Recent unsupervised turbulence mitigation methods have demonstrated the effectiveness of representing a sharp image as an implicit neural representation (INR). However, their tilt and blur representations remain frame-dependent, and the number of optimization parameters grows with the number of input frames. To address this limitation, we propose TriINR, an unsupervised turbulence mitigation method that recovers a sharp image from multiple degraded frames. TriINR represents the sharp image, tilt, and blur as three implicit neural representations. By modeling tilt and blur as spatio-temporal INRs, TriINR achieves frame-count-independent degradation representation and memory-efficient optimization. We further incorporate physical and statistical properties of atmospheric turbulence as constraints on the INRs to improve restoration accuracy. Experiments on synthesized turbulence data with three degradation strengths show that TriINR restores images more robustly across varying turbulence strengths than prior TM methods and achieves the highest accuracy among the evaluated unsupervised methods. Our method also demonstrates robustness on real long-range scenes containing additional non-ideal motion.