No-Reference Quality Assessment Method for Blurriness of SEM Micrographs with Multiple Texture.

Hui Wang,Xiaojuan Hu,Hui Xu,Zhaolin Lu,Shiyin Li

doi:10.1155/2019/4271761

Abstract

Scanning electron microscopy (SEM) plays an important role in the intuitive understanding of microstructures because it can provide ultrahigh magnification. Tens or hundreds of images are regularly generated and saved during a typical microscopy imaging process. Given the subjectivity of a microscopist's focusing operation, blurriness is an important distortion that debases the quality of micrographs. The selection of high-quality micrographs using subjective methods is expensive and time-consuming. This study proposes a new no-reference quality assessment method for evaluating the blurriness of SEM micrographs. The human visual system is more sensitive to the distortions of cartoon components than to those of redundant textured components according to the Gestalt perception psychology and the entropy masking property. Micrographs are initially decomposed into cartoon and textured components. Then, the spectral and spatial sharpness maps of the cartoon components are extracted. One metric is calculated by combining the spatial and spectral sharpness maps of the cartoon components. The other metric is calculated on the basis of the edge of the maximum local variation map of the cartoon components. Finally, the two metrics are combined as the final metric. The objective scores generated using this method exhibit high correlation and consistency with the subjective scores.

Highlights

Scanning electron microscopy (SEM) helps researchers intuitively understand microstructures because it can provide ultrahigh magnification
Postek and Vladár disregarded the characteristics of the human visual system (HVS), which is the final receiver of the images
This study proposes a new no reference (NR) assessment method that initially decomposes SEM micrographs into cartoon and textured components

Summary

Introduction

Scanning electron microscopy (SEM) helps researchers intuitively understand microstructures because it can provide ultrahigh magnification. SEM is playing an increasingly important role in various research areas, such as medical imaging, automated inspection, bioimaging, and ore detection. Images obtained via SEM may be blurred because of the imaging equipment used or the operators who performed the process. Given the subjectivity of the SEM operation, blurring is a major distortion in SEM images [4,5,6]. Postek and Vladár qualitatively and quantitatively analysed the sharpness of micrographs in the Fourier domain [7, 8]. Their research was easy to understand and the meaning was clear. Postek and Vladár disregarded the characteristics of the human visual system (HVS), which is the final receiver of the images.

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