Noise suppression and image enhancement in cold atom absorption imaging

Area of Science:

• Atomic, Molecular & Optical Physics
• Quantum Optics
• Image Processing

Background:

• Noise in cold atom absorption imaging limits measurement accuracy.
• Effective denoising is needed without altering atom cloud structure.

Purpose of the Study:

• Introduce a novel image enhancement algorithm for cold atomic absorption imaging.
• Suppress background noise and enhance image contrast.
• Improve signal-to-noise ratio and measurement uncertainty.

Main Methods:

• Developed a novel, automated image enhancement algorithm.
• Algorithm operates on single images, requiring no reference library.
• No manual parameter selection needed for optimization.

Main Results:

• Significantly suppressed background noise and enhanced image contrast.
• Improved signal-to-noise ratio by approximately 10 dB.
• Enhanced cold atom number measurement uncertainty by tenfold.
• Preserved spatial distribution of atom clouds.
• Demonstrated robustness against fringe noise and multi-component scenarios.

Conclusions:

• The developed algorithm offers effective denoising for cold atom absorption imaging.
• It provides significant improvements in image quality and measurement accuracy.
• The method is automated, practical, and applicable to diverse cold atom imaging fields.