[HTML][HTML] Multi-source information fused generative adversarial network model and data assimilation based history matching for reservoir with complex geologies
For reservoirs with complex non-Gaussian geological characteristics, such as carbonate
reservoirs or reservoirs with sedimentary facies distribution, it is difficult to implement history …
reservoirs or reservoirs with sedimentary facies distribution, it is difficult to implement history …
Single Image Signal-to-Noise Ratio (SNR) Estimation Techniques for Scanning Electron Microscope–A Review
DCY Ong, KS Sim - IEEE Access, 2024 - ieeexplore.ieee.org
Noises are commonly present in grayscale images, particularly in Scanning Electron
Microscope (SEM) images especially secondary emission noise, which can significantly …
Microscope (SEM) images especially secondary emission noise, which can significantly …
[PDF][PDF] Deep convolutional neural network for SEM image noise variance classification
Scanning Electron Microscopy (SEM) image plays a significant role in industrial, medical,
and research fields. However, image defects, including existing noise will degrade the …
and research fields. However, image defects, including existing noise will degrade the …
Unsupervised estimation of the equivalent number of looks in SAR images
Y Cui, G Zhou, J Yang… - IEEE Geoscience and …, 2011 - ieeexplore.ieee.org
In this letter, an unsupervised method for estimating the equivalent number of looks (ENL) in
synthetic aperture radar (SAR) images is proposed. Assuming that the multiplicative noise in …
synthetic aperture radar (SAR) images is proposed. Assuming that the multiplicative noise in …
Signal-to-noise ratio estimation for SEM single image using cubic spline interpolation with linear least square regression
A novel technique based on cubic spline interpolation with linear least square regression
(CSILLSR) is developed to calculate the signal-to-noise ratio (SNR) of scanning electron …
(CSILLSR) is developed to calculate the signal-to-noise ratio (SNR) of scanning electron …
Image signal‐to‐noise ratio and noise variance estimation using autoregressive model
During the last three decades, several techniques have been proposed for signal‐to‐noise
ratio (SNR) and noise variance estimation in images, with different degrees of success …
ratio (SNR) and noise variance estimation in images, with different degrees of success …
Noise variance estimation using image noise cross‐correlation model on SEM images
A number of techniques have been proposed during the last three decades for noise
variance and signal‐to‐noise ratio (SNR) estimation in digital images. While some methods …
variance and signal‐to‐noise ratio (SNR) estimation in digital images. While some methods …
Image signal‐to‐noise ratio estimation using shape‐preserving piecewise cubic Hermite autoregressive moving average model
KS Sim, MY Wee, WK Lim - Microscopy research and technique, 2008 - Wiley Online Library
We propose to cascade the Shape‐Preserving Piecewise Cubic Hermite model with the
Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape …
Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape …
Signal-to-noise ratio (SNR) as a measure of reproducibility: design, estimation, and application
N Elkum, MM Shoukri - Health Services and Outcomes Research …, 2008 - Springer
This paper proposes the use of signal-to-noise ratio (SNR) as another index of a
measurement's reproducibility. We derive its maximum likelihood estimation and discuss …
measurement's reproducibility. We derive its maximum likelihood estimation and discuss …
Signal‐to‐noise ratio estimation on SEM images using cubic spline interpolation with Savitzky–Golay smoothing
A new technique based on cubic spline interpolation with Savitzky–Golay noise reduction
filtering is designed to estimate signal‐to‐noise ratio of scanning electron microscopy (SEM) …
filtering is designed to estimate signal‐to‐noise ratio of scanning electron microscopy (SEM) …