Adaptive Optimizable Gaussian Process Regression Linear Least Squares Regression Filtering Method for SEM Images

Scanning Electron Microscopy (SEM) images often suffer from noise contamination, which degrades image quality and affects further analysis. This research presents a complete approach to estimate their Signal-to-Noise Ratio (SNR) and noise variance (NV), and enhance image quality using NV-guided Wien...

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Vydáno v:	IEEE access Ročník 13; s. 93574 - 93592
Hlavní autoři:	Chee Yong Ong, Dominic, Bukhori, Iksan, Sim, Kok Swee, Beng Gan, Kok
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Electrons Estimation Gaussian process Gaussian process regression (GPR) Gaussian processes Image degradation Image filters Image processing Image quality Interpolation Least squares method Machine learning Noise noise variance estimation Numerical analysis Regression scanning electron microscope (SEM) Scanning electron microscopy Signal to noise ratio signal-to-noise ratio (SNR) SNR estimation support vector machine (SVM) Support vector machines Wiener filtering Wiener filters
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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