Scattering suppression in single-photon imaging based on the combined spatial denoising and K-nearest neighbors...

Area of Science:

• Optics and Photonics
• Remote Sensing
• Signal Processing

Background:

• Imaging through scattering media is challenging due to laser energy loss and prominent scattering noise.
• LiDAR technology offers high resolution and range but is susceptible to scattering effects.
• Existing methods struggle with high attenuation coefficients and unknown noise levels.

Purpose of the Study:

• To develop a photon-limited imaging system for effective imaging through scattering media.
• To propose a novel algorithm for noise suppression and ballistic photon extraction.
• To demonstrate the system's capability in high-attenuation environments.

Main Methods:

• A scanning-based, point-to-point single-photon LiDAR system was developed.
• Single-photon detectors were used to capture extremely weak signals.
• A spatial denoising and K-nearest neighbors (SDKNN) algorithm utilizing time-resolved data was employed.

Main Results:

• The system successfully imaged targets in dense fog with high attenuation coefficients (up to 8.38 m⁻¹).
• The SDKNN algorithm effectively suppressed scattering noise by extracting ballistic photons.
• High-quality imaging was achieved even under harsh weather conditions.

Conclusions:

• The proposed single-photon LiDAR system and SDKNN algorithm provide a robust solution for imaging through scattering media.
• This technique significantly enhances imaging performance in environments with high attenuation.
• The method is suitable for reliable remote sensing applications under adverse weather conditions.