Paper
4 September 2015 Imaging through turbulence using a plenoptic sensor
Author Affiliations +
Abstract
Atmospheric turbulence can significantly affect imaging through paths near the ground. Atmospheric turbulence is generally treated as a time varying inhomogeneity of the refractive index of the air, which disrupts the propagation of optical signals from the object to the viewer. Under circumstances of deep or strong turbulence, the object is hard to recognize through direct imaging. Conventional imaging methods can’t handle those problems efficiently. The required time for lucky imaging can be increased significantly and the image processing approaches require much more complex and iterative de-blurring algorithms. We propose an alternative approach using a plenoptic sensor to resample and analyze the image distortions. The plenoptic sensor uses a shared objective lens and a microlens array to form a mini Keplerian telescope array. Therefore, the image obtained by a conventional method will be separated into an array of images that contain multiple copies of the object’s image and less correlated turbulence disturbances. Then a highdimensional lucky imaging algorithm can be performed based on the collected video on the plenoptic sensor. The corresponding algorithm will select the most stable pixels from various image cells and reconstruct the object’s image as if there is only weak turbulence effect. Then, by comparing the reconstructed image with the recorded images in each MLA cell, the difference can be regarded as the turbulence effects. As a result, the retrieval of the object’s image and extraction of turbulence effect can be performed simultaneously.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chensheng Wu, Jonathan Ko, and Christopher C. Davis "Imaging through turbulence using a plenoptic sensor", Proc. SPIE 9614, Laser Communication and Propagation through the Atmosphere and Oceans IV, 961405 (4 September 2015); https://doi.org/10.1117/12.2190975
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Turbulence

Sensors

Image sensors

Image processing

3D image processing

Atmospheric turbulence

Cameras

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