Three-dimensional imaging reconstruction algorithm of gated-viewing laser imaging with compressive sensing

Area of Science:

• Optics and Photonics
• Computational Imaging
• Signal Processing

Background:

• Three-dimensional (3D) laser imaging offers advantages like low power consumption and reduced sensor count.
• Combining 3D imaging with compressive sensing (CS) presents computational challenges for processing devices.
• Existing methods require significant computational resources for CS recovery.

Purpose of the Study:

• To develop a computationally efficient 3D imaging reconstruction algorithm for time-slice images.
• To reduce the computational load associated with compressive sensing (CS) recovery in 3D imaging.
• To enhance the performance of 3D laser imaging systems utilizing single-pixel detectors.

Main Methods:

• A novel algorithm is proposed that prioritizes 3D imaging reconstruction before CS recovery.
• The method processes time-slice images acquired by single-pixel detectors.
• Algorithm performance is validated through experimental simulations.

Main Results:

• The proposed algorithm demonstrates superior efficiency compared to existing methods.
• Implementing 3D reconstruction prior to CS recovery significantly reduces runtime.
• Simulation results confirm the enhanced performance of the novel approach.

Conclusions:

• The developed fast 3D imaging reconstruction algorithm offers a more efficient solution for single-pixel detector systems.
• Reordering the reconstruction process (3D imaging before CS recovery) effectively mitigates computational stress.
• This approach enhances the practical applicability of 3D laser imaging systems.