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No-Reference Quality Assessment Method for Blurriness of SEM Micrographs with Multiple Texture
Hui Wang1, Xiaojuan Hu2, Hui Xu3
1School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.
Scanning
|July 9, 2019
Summary
This study introduces an automated method to assess micrograph blurriness in scanning electron microscopy (SEM). The new technique objectively identifies high-quality images, saving time and effort compared to manual selection.
Area of Science:
- Materials Science
- Microscopy Imaging
- Image Quality Assessment
Background:
- Scanning electron microscopy (SEM) is crucial for microstructure analysis, generating numerous images.
- Image blurriness is a common distortion affecting micrograph quality.
- Manual selection of high-quality micrographs is subjective, time-consuming, and costly.
Purpose of the Study:
- To develop a no-reference objective method for evaluating SEM micrograph blurriness.
- To provide an automated solution for selecting high-quality micrographs.
Main Methods:
- Decomposition of micrographs into cartoon and textured components based on human visual perception.
- Extraction of spectral and spatial sharpness maps from cartoon components.
- Calculation of two metrics based on sharpness maps and local variation, combined for a final objective score.
Main Results:
- The proposed objective scoring method shows high correlation with subjective quality assessments.
- The method effectively quantifies micrograph blurriness.
Conclusions:
- The developed objective method offers a reliable and efficient alternative to manual micrograph quality assessment.
- This technique can significantly improve the efficiency of SEM image analysis workflows.
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