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An imaging-based approach to measure atmospheric turbulence

The dissipation and bending of light waves by atmospheric turbulence adversely affects infrared imaging, leading to grayscale drift, distortion, and blurring. A deep learning method has been developed to both extract the two-dimensional atmospheric turbulence strength fields and obtain clear and stable images from turbulence-distorted infrared images.

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Fig. 1: Overview of the PBCL framework.


  1. Dutton, J. A. & Panofsky, H. A. Clear air turbulence: A mystery may be unfolding: High altitude turbulence poses serious problems for aviation and atmospheric science. Science 167, 937–944 (1970). This article introduces the importance of atmospheric turbulence for aviation and atmospheric science and points out that careful measurements and data processing are needed to understand it.

    Article  Google Scholar 

  2. Browning, K. & Watkins, C. Observations of clear air turbulence by high power radar. Nature 227, 260–263 (1970). This article presents the vertical soundings of atmospheric turbulence using a high-power radar.

    Article  Google Scholar 

  3. Sathe, A. & Mann, J. A review of turbulence measurements using ground-based wind lidars. Atmos. Meas. Tech. 6, 3147–3167 (2013). A review article that summarizes turbulence measurements obtained using ground-based wind lidars.

    Article  Google Scholar 

  4. Zhu, X. & Milanfar, P. Removing atmospheric turbulence via space-invariant deconvolution. IEEE T. Pattern. Anal. 35, 157–170 (2012). This article presents a method that restores a clear image from an image sequence distorted by atmospheric turbulence using multi-frame registration and fusion.

    Article  Google Scholar 

  5. Jin, D. et al. Neutralizing the impact of atmospheric turbulence on complex scene imaging via deep learning. Nat. Mach. Intell. 3, 876–884 (2021). This article presents a deep learning-based method that neutralizes the effects of atmospheric turbulence on imaging data.

    Article  Google Scholar 

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This is a summary of: Wang, Y. et al. Revelation of hidden 2D atmospheric turbulence strength fields from turbulence effects in infrared imaging. Nat. Comput. Sci. (2023).

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An imaging-based approach to measure atmospheric turbulence. Nat Comput Sci 3, 673–674 (2023).

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