Gamma Correction and Color Space Transformations for Quantitative Analysis of Electrochemiluminescence Images Using...

Area of Science:

• Analytical Chemistry
• Biomedical Imaging
• Spectroscopy

Background:

• Consumer digital cameras are increasingly used for quantitative imaging of luminescent signals.
• Challenges include device variability, nonlinear encoding, and lack of standardized workflows, hindering reproducibility.
• Accurate quantification is crucial for applications in diagnostics and biosensing.

Purpose of the Study:

• To develop a generalized methodology for robust, device-independent signal quantification in luminescent systems using digital imaging.
• To address limitations of current consumer-grade camera-based quantification methods.
• To establish standardized workflows for high-throughput optical analysis.

Main Methods:

• Combined synchronized electrochemical control with manual optimization of imaging parameters.
• Applied gamma correction and color space transformations (RGB, CIEXYZ, CIELAB) for device-independent analysis.
• Evaluated different color channels for sensitivity and dynamic range using Ru-(bpy)3 2+/TPrA as a model system.

Main Results:

• Linearized r and X channels offer broad dynamic range with moderate sensitivity.
• Encoded R and a* channels show higher sensitivity at low concentrations but require nonlinear modeling.
• The methodology enables accurate quantification across different color spaces and modeling approaches.

Conclusions:

• The developed scalable approach facilitates standardized, high-throughput optical analysis using low-cost camera platforms.
• This methodology improves reproducibility and accuracy in quantitative luminescent imaging.
• Broad applications are anticipated in diagnostics, biosensing, and analytical chemistry.