New technique for in-situ measurement of backscattered and secondary electron yields for the calculation of signal-to-noise ratio in a SEM

Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error

A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time.

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) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time.

Image noise cross-correlation for signal-to-noise ratio estimation in scanning electron microscope images

A new and robust parameter estimation technique, named image noise cross-correlation, is proposed to predict the signal-to-noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with nearest neighborhood and first-order interpolation. Overall, the proposed method is best as its estimations for the noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree, compared with the others.

Unusual secondary electron emission behavior in carbon nanotube forests

Electron yield was measured from patterned carbon nanotube forests for a wide range of primary beam energies (400-20,000 eV). It was observed that secondary and backscattered electron emission behaviors in these forests are quite different than in bulk materials. This seems to be primarily because of the increased range of electrons due to the porous nature of the forests and dependent on their structural parameters, namely nanotube length, diameter and inter-nanotube spacing. In addition to providing insight into the electron microscopy of nanotubes, these results have interesting implications on designing novel secondary electron emitters based on the structural degrees of freedom of nanomaterials.

Gaussian-Taylor signal-to-noise ratio estimation for scanning electron microscope images

A new and robust parameter estimation technique, named Gaussian-Taylor interpolation, is proposed to predict the signal-to-noise ratio (SNR) of scanning electron microscope images. The results of SNR and variance estimation values are tested and compared with piecewise cubic Hermite interpolation, quadratic spline interpolation, autoregressive moving average and moving average. Overall, the proposed estimations for noise-free peak and SNR are most consistent and accurate to within a certain acceptable degree compared with the others.

Real-time image quality assessment with mixed Lagrange time delay estimation autoregressive (MLTDEAR) model

A proposal to assess the quality of scanning electron microscope images using mixed Lagrange time delay estimation technique is presented. With optimal scanning electron microscope scan rate information, online images can be quantified and improved. The online quality assessment technique is embedded onto a scanning electron microscope frame grabber card for real-time image processing. Different images are captured using scanning electron microscope and a database is built to optimally choose filter parameters. An optimum choice of filter parameters is obtained. With the optimum choice of scan rate, noise can be removed from real-time scanning electron microscope images without causing any sample contamination or increasing scanning time.

Autoregressive Wiener filtering in a scanning electron microscopy imaging system

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 images prior to filter implementation. The resultant filter is called AR-Wiener filter. The proposed filter is embedded onto the frame grabber card of the scanning electron microscope (SEM) for real-time image processing. Different images are captured using SEM and used to compare the performances of the conventional Wiener and the proposed AR-Wiener technique.