Noise reduction of SEM images using adaptive Wiener filter
Nazanin Arazm, Alireza Sahab, Mehdi Fallah Kazemi · 2017
In this paper, we propose an improved pixel-wise adaptive Wiener filter to suppress additive white Gaussian noise in scanning electron microscope (SEM) images. We employ an adaptive weight function (AWF), to estimate local spatial statistics of Wiener filter. In this AWF, the estimation of noise variance is required, so we use the linear regression (LR) method to estimate noise variance. Finally, the proposed filter is compared with original Wiener filter and another existence Wiener filter to denoise SEM images. For different noise variances, experimental results indicate that proposed filter has better performance in comparison with other mentioned filters.