Nidal Kamel

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In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor(More)
Component Analysis (PCA) to extract Visual Evoked Potential (VEP) signals, the selection of principal components (PCs) is an important issue. We propose a new method here that selects only the appropriate PCs. We denote the method as selective eigen-rate (SER). In the method, the VEP is reconstructed based on the rate of the eigen-values of the PCs. When(More)
In this paper, we propose to use the autoregressive (AR)-based interpolator with Wiener filter and apply the idea to scanning electron microscope (SEM) images. The concept for combining the AR-based interpolator with Wiener filtering comes from the essential requirement of Wiener filtering for accurate and consistent estimation of the power of the noise in(More)
Here we give proof to the best suitable normalization method for the Selective Eigen Rate (SER) a novel technique, that is used in selecting only the higher rate of principal components (PCs) for using them in Principal Component Analysis (PCA) while separating Visual Evoked Potential (VEP) from electroencephalogram (EEG) signals, to enable single trial(More)
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. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image.(More)
In single trial source separation problem of VEP signals, the selection of legitimate Principal Components (PCs) is an important phenomenon. The Spectral Power Ratio (SPR) method developed by us earlier for PCA has proven to be capable of selecting only the required PCs in a sophisticated manner. Our continuous enhancement has lead to the current(More)
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