Signal Perception in Two-Dimensional Mapping Techniques: Just Noticeable Difference as a Visual Limit of Detection

Area of Science:

• Analytical Chemistry
• Chemical Imaging
• Instrumental Methods

Background:

• The limit of detection (LOD) is a standard metric for instrumental performance, often calculated as three times the standard deviation of the blank.
• In 2D elemental imaging and mapping, signals below the LOD can still be visually detected, posing a challenge for accurate analysis.
• Existing methods may not fully utilize the visual information present in 2D datasets.

Purpose of the Study:

• To introduce the Just-Noticeable Difference (JND), a concept from psychophysics, as a novel figure of merit for 2D chemical data analysis.
• To propose JND as an alternative to the traditional LOD for assessing detection limits in elemental imaging and mapping.
• To enhance the sensitivity and accuracy of elemental concentration assessments in spatially resolved datasets.

Main Methods:

• Utilizing the theory of psychophysics to define and apply the Just-Noticeable Difference (JND) to 2D chemical data.
• Applying the JND approach to elemental mapping techniques, specifically Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) and Laser-Induced Breakdown Spectroscopy (LIBS).
• Comparing the performance of the JND metric against the standard LOD metric for analyzing low-contrast signals and spatial information.

Main Results:

• The JND approach demonstrates enhanced sensitivity for detecting spatially resolved signals across various sizes and noise levels in 2D datasets.
• The JND metric provides an alternative to the LOD, potentially leading to more accurate assessments of elemental concentrations.
• The study highlights the improved utilization of contrast variations and spatial information inherent in mapping techniques when using JND.

Conclusions:

• The Just-Noticeable Difference (JND) offers a promising alternative to the traditional LOD for 2D chemical data analysis, particularly in elemental imaging and mapping.
• Implementing JND can lead to more accurate elemental concentration measurements and better exploitation of spatial data.
• This psychophysics-inspired approach advances the characterization of instrumental performance in complex chemical datasets.