Computational Ghost Imaging Based on Light Source Formed by Coprime Array.

Area of Science:

• Optics and Photonics
• Computational Imaging
• Signal Processing

Background:

• Spatial light modulators (SLMs) are crucial for modulating light fields in computational ghost imaging.
• Current SLM pixel arrangements (uniform or random sparse) have limitations, including periodicity and background noise, affecting imaging quality.
• Optimizing pixel arrangement is key to enhancing ghost imaging performance.

Purpose of the Study:

• To introduce and evaluate a novel coprime array based on Eisenstein integers for spatial light modulator pixel arrangement in computational ghost imaging.
• To demonstrate the advantages of this new arrangement over traditional uniform and random sparse patterns.
• To improve imaging quality, reduce background noise, and avoid periodicity in ghost imaging.

Main Methods:

• Development of a coprime array structure utilizing Eisenstein integers for SLM pixel arrangement.
• Implementation of this coprime array in a computational ghost imaging framework.
• Numerical simulations to compare imaging performance against uniform and random sparse arrays.

Main Results:

• The proposed coprime array significantly enhances imaging quality, especially with limited measurements.
• This arrangement effectively reduces background noise compared to random sparse patterns.
• Periodicity issues inherent in uniform arrays are successfully avoided.

Conclusions:

• The coprime array based on Eisenstein integers represents a significant advancement for spatial light modulator design in computational ghost imaging.
• This method offers a superior approach to pixel arrangement, leading to improved image fidelity and reduced artifacts.
• The findings pave the way for more robust and efficient ghost imaging systems.