High-fidelity and efficient particle microscopy via regional focus search and adaptive focus stacking

Area of Science:

• Materials Science
• Optical Imaging
• Nanotechnology

Background:

• Micro-nano particle characterization is crucial for product performance.
• Image-based detection is challenged by focus variations affecting particle feature accuracy.

Purpose of the Study:

• To develop a method for generating high-resolution particle images for accurate detection.
• To improve the characterization of micro-nano particles by enhancing image clarity and detail.

Main Methods:

• Utilized focus stacking technology combined with a focused search method.
• Developed an image sharpness evaluation function and particle size measurement standard.
• Reconstructed single images from multiple focal point images.

Main Results:

• Achieved average particle size errors of 2.23%, 1.39%, and 1.89% for mixed polystyrene suspensions.
• Demonstrated significantly lower errors compared to pre-reconstruction images.
• Successfully differentiated particles by size using texture features, yielding bimodal distributions.

Conclusions:

• The proposed focus stacking method enhances particle image resolution and detail.
• This technique improves the accuracy of particle size and shape detection.
• The method offers a more precise representation of particle size data for micro-nano particle analysis.