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The second type of the most frequently encountered image distortion is due to the Gaussian noise arising during acquisition and caused by the intrinsic thermal and electronic fluctuations in camera sensors. This type of noise is evenly distributed over the image and each pixel is distorted by adding...
Statistics and reproducibility We performed statistical analyses using JMP Pro Software (version 14, SAS), unless otherwise indicated. Data were evaluated for normality using a Q–Q plot. For normally distributed data, an ANOVA was used, and a Tukey’s honestly significant different post hoc testin...
The test statistics in this paper are closely related to the statistics literature on tests for goodness of fit and global hypothesis tests in the Gaussian white noise model. Dumbgen and Spokoiny (2001) consider a test related to the test statistic used in the present paper in a one dimensi...
(if the observed noise is not independent and identically distributed (i.i.d.)). Proper thresholds in edge detection and image segmentation depend on noise statistics as well [1,10]. In lossy image compression, a quantization step has to be adaptively adjusted depending on noise variance [11...
more easily separated from the noise [13,14,15]. Another thread of methods is to capture image statistics directly in the image domain [16,17]. Both of the two categories of approaches can produce some good quality images. But the denoised image tends to lose some of its edge information...
Further analysis would be needed to determine whether such a mechanism could produce slowdowns distributed over such a wide temporal span (2–3 words). The incremental processing account, by contrast, is based on the assumption that predictability affects not perception, but the speed of cognitive...
This section contains feature-level insights into the change in the selected feature's distribution, and other statistics, over time. The target dataset is also profiled over time. The statistical distance between the baseline distribution of each feature is compared with the target dataset's over...
Supercontinuum (SC) generated with all-normal dispersion (ANDi) fibers has been of special interest in recent years due to its potentially superior coherence properties when compared to anomalous dispersion-pumped SC. However, care must be taken in the d
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,