Fast and accurate sCMOS noise correction for fluorescence microscopy

Area of Science:

• Biomedical Optics
• Microscopy Technology
• Image Processing

Background:

• Scientific CMOS (sCMOS) sensors offer advanced performance in optical microscopy.
• However, sCMOS sensors introduce readout and pattern noise, degrading image quality and hindering quantification.
• Existing noise reduction methods struggle to preserve fine signal details.

Purpose of the Study:

• To develop an automated algorithm for correcting sCMOS-related noise in fluorescence microscopy.
• To improve the performance of sCMOS cameras for biomedical imaging applications.
• To enable fast, low-light, and quantitative optical microscopy with reduced artifacts.

Main Methods:

• A content-adaptive algorithm for automatic correction of sCMOS noise (ACsN) was developed.
• The algorithm integrates camera physics principles with layered sparse filtering.
• ACsN targets and reduces dominant noise sources specific to sCMOS sensors.

Main Results:

• ACsN significantly reduces sCMOS-related noise.
• The algorithm effectively preserves fine signal details and structural integrity.
• Demonstrated improved camera performance for quantitative fluorescence microscopy.

Conclusions:

• ACsN provides effective, automated noise correction for sCMOS fluorescence microscopy.
• The method enhances imaging capabilities for low-light and high-speed applications.
• Enables more reliable quantitative analysis and reduces photo-damage in live samples.