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Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

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Published on: February 8, 2014

High-resolution far-field ghost imaging via sparsity constraint.

Wenlin Gong¹, Shensheng Han¹

¹Key Laboratory for Quantum Optics and Center for Cold Atom Physics of CAS, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, 201800, China.

Scientific Reports

|March 20, 2015

Summary

This summary is machine-generated.

Ghost imaging via sparsity constraint (GISC) enhances imaging resolution by leveraging object sparsity and compressive sensing. This method achieves high-resolution imaging even with limited measurements, outperforming conventional ghost imaging.

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Last Updated: Apr 16, 2026

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Published on: February 8, 2014

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Published on: January 6, 2026

Area of Science:

Optics and Photonics
Computational Imaging
Signal Processing

Background:

Conventional ghost imaging (GI) resolution is limited by speckle size.
Nonlocal imaging with single-pixel detectors is a key feature of GI.
Existing GI reconstruction algorithms face resolution constraints.

Purpose of the Study:

To enhance the imaging resolution of ghost imaging.
To demonstrate ghost imaging via sparsity constraint (GISC) experimentally.
To investigate factors influencing high-resolution GISC.

Main Methods:

Combining ghost imaging with sparsity constraints.
Utilizing compressive sensing for image reconstruction.
Experimental investigation of GISC performance and influencing factors.

Main Results:

GISC dramatically enhances imaging resolution compared to conventional GI.
High-resolution imaging achieved with measurements below the Nyquist limit.
Numerical aperture and sparse representation basis impact reconstruction quality.

Conclusions:

GISC offers a significant resolution improvement for ghost imaging.
The technique is robust even with sub-Nyquist sampling.
GISC holds promise for applications in microscopy and remote sensing.