Imaging through Atmospheric Turbulence
Overview
Imaging through atmospheric turbulence is a fundamental problem for long-range imaging systems. Purdue i2Lab has specialities in several aspects of the subject:
Book
Stanley H. Chan and Nicholas Chimitt, Computational Imaging through Atmospheric Turbulence , Now Publisher 2023.
Tutorial
Recordings
VIDEO
VIDEO
VIDEO
VIDEO
Purdue Atmospheric Turbulence Simulator
Phase-over-aperture model (Version 1)
Phase-to-space transform (Version 2)
Key Concept : Transform Zernike representation to PSF representation. 1000x speed up compared to split-step.
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Code :
Project Page : project_turbulence_TurbSim_v2.html
Dense field phase-to-space transform (Version 3)
Key concept : Quantize and decouple Zernike mode and spatial mode to preserve wide sense stationarity. Enables full HD without interpolation.
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Arbitrary Cn2 Profile (Version 4)
Key concept : Integrate Cn2 along the path instead of evaluating individual turbulence segments
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Scattering and Gathering for Spatially Varying Convolutions (Version 5)
Key finding : Scattering is for optics simulation, whereas gathering is for signal filtering
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Turbulence Reconstruction
Classical optimization-based approach
Key concept : Lucky imaging + blind deconvolution
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MATLAB Code :
[Project Page]
TurbNet: Single-frame Turbulence Reconstruction
Key concept : Re-blur the reconstructed image using a turbulence simulator
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Code :
PiRN: Physics-integrated Restoration Network
Turbulence Mitigation Transformer
Key concept : Two-stage mitigation, transformer, temporal attention
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Code :
Theoretical Analysis
Tilt-then-Blur or Blur-then-Tilt
Key conclusion : Tilt + blur is the correct model
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