Key Takeaways & Executive Findings
- •• This study provides a comprehensive numerical analysis of factors affecting localization precision and resolution in single emitter localization-based imaging systems, incorporating more parameters than previous studies. • It distinguishes the effects of additive and multiplicative noise on localization precision, and quantifies the influence of sampling frequency, offering optimal sampling frequency values for different resolution needs. • The paper establishes guidelines for selecting signal-to-noise ratio (SNR) and pixel size based on point spread function (PSF) width, enabling better system design for super-resolution imaging. • The findings offer critical theoretical and practical insights for optimizing more complex imaging systems beyond single emitter localization.
Abstract
In this paper, we numerically analyze the factors determining localization precision and resolution in single emitter localization-based imaging systems. While previous studies have considered a limited set of parameters, our numerical approach incorporates additional parameters with significant reference values, yielding a more comprehensive analysis of the results. We differentiate between the effects of additive and multiplicative noise on localization precision using numerical modeling and take the influence of the sampling frequency into account, computing the optimal sampling frequency for varying resolution requirements. Leveraging a suite of derived equations, we systematically simulate and quantify how variations in these parameters influence system performance. Furthermore, we provide guidelines for optimizing signal-to-noise ratio (SNR) requirements and pixel size selection based on point spread function (PSF) width in single emitter localization-based imaging systems. This numerically driven research offers critical insights for the analysis of more complex imaging systems.
1. Introduction
Resolution is a fundamental parameter in optical imaging systems, directly determining the amount of information a system can capture. Researchers have long focused on methods to improve it. However, resolution enhancement is constrained by the Abbe diffraction limit; when passing through the optical system, an ideal point object becomes a spot due to diffraction, meaning that two closely spaced points may become indistinguishable. Efforts have been made to overcome the diffraction limit barrier using various approaches. Stimulated emission depletion microscopy (STED) and structured illumination microscopy (SIM) have improved the resolution through point spread function (PSF) engineering and frequency-domain analysis.
Additionally, single-molecule localization microscopy (SMLM) sidesteps the need to resolve two points by focusing on single-point imaging. In SMLM, the center position of each individual spot can be determined with greater precision than the spot size. The localization precision and accuracy of single-point positioning methods have been extensively studied, providing a solid theoretical and experimental foundation for understanding the limits of spatial resolution in fluorescence microscopy. The relationship between the localization precision and resolution is described by Rlimit = 2√(2ln2) Δx ≈ 2.35 Δx, offering a method to circumvent the system’s diffraction limit and enabling higher imaging resolution.
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Yueying WANG, Yiwen HU, Yuehan ZHAO, Cuifang KUANG, Xiang HAO (2025). Numerical investigation of resolution in single emitter localization-based imaging systems. Frontiers of Information Technology & Electronic Engineering. https://doi.org/10.1631/FITEE_2500015
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Frequently Asked Questions
What is the main focus of this paper?
The paper numerically investigates the factors that determine localization precision and resolution in single emitter localization-based imaging systems, such as SMLM, and provides guidelines for optimizing system parameters.
How does this study differ from previous analyses?
Unlike earlier studies that considered a limited set of parameters, this work incorporates additional parameters including additive and multiplicative noise and sampling frequency, leading to a more comprehensive analysis.
What is the significance of the relationship Rlimit ≈ 2.35 Δx?
This relationship connects the resolution limit to localization precision, showing that by achieving high localization precision, one can overcome the diffraction limit and achieve higher imaging resolution.
What practical guidelines does the paper provide?
The paper offers guidelines for optimizing signal-to-noise ratio (SNR) requirements and pixel size selection based on point spread function (PSF) width, which are critical for designing high-performance imaging systems.
Why is sampling frequency important in this context?
Sampling frequency affects localization precision; the paper computes optimal sampling frequencies for different resolution requirements, helping to balance data acquisition and resolution.
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