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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

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Related Experiment Video

Updated: Nov 1, 2025

Measurement of Scattering Nonlinearities from a Single Plasmonic Nanoparticle

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Published on: January 3, 2016

Sub-Nyquist ghost imaging by optimizing point spread function.

|June 22, 2021

Summary

This summary is machine-generated.

Optimized ghost imaging (OGI) enhances image quality by modifying speckle patterns. This method achieves stable object recovery and improved signal-to-noise ratio (SNR) even with limited measurements, outperforming traditional ghost imaging techniques.

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Last Updated: Nov 1, 2025

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Published on: January 3, 2016

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Area of Science:

Optics and Photonics
Computational Imaging

Background:

Traditional ghost imaging (GI) using pseudo-thermal light sources suffers from a non-space-translation-invariant point spread function (PSF).
Existing GI linear reconstruction algorithms yield low-quality images when measurement processes are not ergodic, limiting practical applications.

Purpose of the Study:

To optimize the PSF property in ghost imaging.
To develop a novel linear reconstruction method for stable image recovery under non-ergodic conditions and below the Nyquist limit.

Main Methods:

Modification of intensity values in speckle patterns recorded by the reference path camera.
Development and application of the optimized ghost imaging (OGI) linear reconstruction algorithm.

Main Results:

OGI optimizes the PSF, enabling stable object image recovery even with measurements below the Nyquist limit.
Simulated and experimental results show significant enhancement in image signal-to-noise ratio (SNR) with OGI.
Performance improvements are particularly notable when the sampling ratio exceeds 0.68 and detection SNR is above 20 dB.

Conclusions:

Optimized ghost imaging (OGI) provides a robust solution for improving image quality in ghost imaging systems.
The proposed method overcomes limitations of traditional GI algorithms, especially in scenarios with insufficient data or non-ideal measurement conditions.