Restoration is the main process in many applications. Restoring an original image from a damaged image is the foundation of the restoring operation, either blind or non-blind. One of the main challenges in the restoration process is to estimate the degradation parameters. The degradation parameters include Blurring Function (Point Spread Function, PSF) and Noise Function. The most common causes of image degradation are errors in transmission channels, defects in the optical system, inhomogeneous medium, relative motion between object and camera, etc. In our research, a novel algorithm was adopted based on Circular Hough Transform used to estimate the width (radius, sigma) of the Point Spread Function. This algorithm is based on the PSF, which represents the redistribution of energy in the image plane of a point source located in the object plane. A second novel algorithm was adopted to estimate the variance of the added noise, based on dividing the degraded image into sub homogeneous images. The result shows that these two algorithms give excellent results for estimating the PSF and Noise Variance, and for different values of PSF widths and Noise variances, compared to real PSF widths and Noise Variances values.
Background: The aim of this in vitro study was to evaluate and compare the effect of preheating microleakage among three different filler size composites which include Filtektm Z250 micro hybrid, Z250xt Nano hybrid and nanocomposite Z350xt. in Class II cavity preparation .
Materials and methods: sixty maxillary first premolars were prepared with class II cavities. Samples were divided into three groups according to material used group A (FiltekZ250 micro hybrid). Group B(Z250xt Nano hybrid). Group C (nanocomposite Z350xt)and each group divided into two subgroups of ten teeth according to temperature of composite:
... Show MoreResearchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
... Show MoreIn this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
In this research , we study the inverse Gompertz distribution (IG) and estimate the survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes
Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .
In this paper a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet
... Show MoreIn this study, the plasma formed by the preparation of Se and Tin (Sn) using a Nd: YAG laser with a wavelength of 1064 nm in air, which was then studied using the technique of optical emission spectrum, was presented (OES).The laser-induced plasma parameters such an electron temperature (Te) were identified using two-ratio methods, using Stark broadening methods to determine the density of electrons (ne). According to the findings, there is a correlation between the amount of laser energy that is applied and the increase in the emission intensity of the spectral lines. In the case of Se plasma, an increase in laser energy causes a rise in the temperature of the electrons. While increasing the temperature of the elec
... Show MoreThis paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).
The cutting transport problem in the drilling operation is very complex because many parameters impact the process, which is nonlinearity interconnected. It is an important factor affecting time, cost and quality of the deviated and horizontal well. The main objective is to evaluate the influence of main drilling Parameters, rheological properties and cuttings that characterise lifting capacity through calculating the minimum flow rate required and cutting bed height and investigate these factors and how they influenced stuck pipe problems in deviated wells for Garraf oil field. The results obtained from simulations using Well Plan™ Software were showed that increasing viscosity depends on other conditions for an increase or dec
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