The Enhanced Thematic Mapper Plus (ETM+) that loaded onboard the Landsat-7 satellite was launched on 15 April 1999. After 4 years, the image collected by this sensor was greatly impacted by the failure of the system’s Scan Line Corrector (SLC), a radiometry error.The median filter is one of the basic building blocks in many image processing situations. Digital images are often distorted by impulse noise due to errors generated by the noise sensor, errors that occur during the conversion of signals from analog-to-digital, as well as errors generated in communication channels. This error inevitably leads to a change in the intensity of some pixels, while some pixels remain unchanged. To remove impulse noise and improve the quality of the image we are working on. In this paper, the Landsat -7 data was corrected from line droop out radiometric errors using the median filter method. we studied the median filter and offer a method based on an improved median filtering algorithm, [2]. We apply the median filter (3 x 3) to correct the image taken by of Landsat 7 and correct it, and we will restore the damaged pixels using the Erdas imagine program.
م.د. فاطمة حميد ،أ.م.د وفاء صباح محمد الخفاجي, International Journal of Psychosocial Rehabilitation,, 2020 - Cited by 1
S Ali…, Journal of Physical Education, 2019 - Cited by 1
The reason for applying the project is for the development of some physiological variables and skill performance using a device for the first time applied in Iraq to a sample of badminton players, and this device has a patent on 7/2/2019. An experimental method is used for a sample of (12) players from (Al-Orthodoxy club). The experimental group is applied the proposal technique, while, the control group is instructed by the coach.The results of the research attribute to the role of the proposal exercises of fit light technology, thus, this technology has increased the attention and focusing of the sample and some physiological variables and smash shot skill. It has been concluded that the exercises using fit light technology is helped to i
... Show MoreDirect FIA methods for estimation of Naringenin (NG) in different samples were proposed. These methods are based on diazotization coupling reactions of two reagents: method (A) p-chloroaniline (PCA) and method (B) procaine hydrochloride (PRH) with NG in basic medium. Yellow dyes with maximum absorption at 416 and 415 nm were formed respectively. Calibration curves were constructed over different NG concentrations, linearity was from 1- 70 and 1- 40 µgmL-1 with detection limits of 0.55 and 0.24 µgmL-1 for (A) and (B) respectively. All analytical variables involved in the FIA procedure were evaluated and optimized. The established methods were successfully applied for the determination of NG in its supplements and u
... Show MoreThis paper is devoted to compare the performance of non-Bayesian estimators represented by the Maximum likelihood estimator of the scale parameter and reliability function of inverse Rayleigh distribution with Bayesian estimators obtained under two types of loss function specifically; the linear, exponential (LINEX) loss function and Entropy loss function, taking into consideration the informative and non-informative priors. The performance of such estimators assessed on the basis of mean square error (MSE) criterion. The Monte Carlo simulation experiments are conducted in order to obtain the required results.
Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin
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