Speckle imaging through turbulent atmosphere based on adaptable pupil segmentation.

Area of Science:

• Optical physics
• Atmospheric optics
• Adaptive optics

Background:

• Turbulence in atmospheric paths significantly degrades image resolution.
• Traditional imaging techniques struggle to overcome atmospheric distortion.

Purpose of the Study:

• To investigate adaptable multiaperture imaging for enhanced resolution through atmospheric turbulence.
• To demonstrate the effectiveness of adaptive subaperture sizing and image deconvolution.

Main Methods:

• Utilized adaptable multiaperture imaging techniques.
• Implemented adaptive matching of subaperture size to turbulence characteristics.
• Applied deconvolution of simultaneously registered subimages.
• Considered various multiaperture geometries: pupil multiplication, pupil image sampling, and plenoptic telescope.

Main Results:

• Achieved resolution improvement on a ~550 m horizontal turbulent path.
• Demonstrated the benefit of adaptively matching subaperture size to turbulence.
• Showcased further gains through deconvolution of multiple subimages.
• Confirmed effectiveness using aperture sampling, speckle image processing, and frame selection.

Conclusions:

• Adaptable multiaperture imaging offers a viable solution for high-resolution imaging through atmospheric turbulence.
• The combination of adaptive techniques and image processing significantly enhances imaging performance.
• This approach holds promise for various applications requiring clear atmospheric imaging.