Motion-enhanced resolution in dynamic single-pixel imaging.

Area of Science:

• Optics and Imaging
• Computational Imaging
• Signal Processing

Background:

• Single-pixel imaging (SPI) utilizes a single detector and structured illumination for flexible image reconstruction across spectral bands.
• Object or platform motion during SPI acquisition is typically considered a source of image degradation and blurring.
• Existing SPI methods focus on mitigating motion artifacts to preserve image quality.

Purpose of the Study:

• To reframe object motion in SPI not as a detriment, but as a beneficial source of sub-pixel sampling diversity.
• To develop a method for accurately tracking translational motion and incorporating it into the SPI forward model.
• To demonstrate enhanced image resolution and fidelity in dynamic scenes by leveraging motion information.

Main Methods:

• Developed a motion tracking technique using geometric moment illumination patterns fused with Hadamard patterns.
• Encoded accurately tracked translational motion into the SPI forward model as structured perturbations.
• Incorporated motion information directly into the inverse problem, solved via total variation minimization.

Main Results:

• Demonstrated that motion can be harnessed as a valuable imaging resource, increasing sampling density beyond the native grid.
• Achieved enhanced-resolved image reconstruction by treating motion as a beneficial factor.
• Obtained finer image details compared to SPI reconstructions from stationary targets.

Conclusions:

• Object motion in SPI can be transformed from a blurring nuisance into a resource for improving resolution and fidelity.
• The proposed method effectively leverages motion to enhance the sampling density and reconstruct finer image details.
• This paradigm shift opens new possibilities for high-fidelity imaging in dynamic scenes using single-pixel imaging techniques.