Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

In the present work, a first-row divalent d-transition metal obtained from curcumin(Curc) and L-3,4-dihydroxyphenylalanin(L-dopa)have been synthesized which their complexes and characterized by C.H.N, conductance, spectral methods: FT-IR, Ultra–Visible. Magneto-chemical measurements, molar conductance ΛM (1×10−3 mol/L in DMSO):36- 0.84 ohm-1.cm2.mol-1 (non-electrolyte). The data shows that the complexes have the structure [M((II))-(Curc)-(L-dopa)] system. Electronic and magnetic data suggest an octahedral geometry for all complexes in which the (L-dopa) and curcumin act as bidentate ligands. Curcumin coordinated to the metal ions M (II) through the lone pair of electrons of oxygen in 2(C=O) groups. The (L-dopa) coordinated to M (II) a

This paper reports the effect of Mg doping on structural and optical properties of ZnO prepared by pulse laser deposition (PLD). The films deposited on glass substrate using Nd:YAG laser (1064 nm) as the light source. The structure and optical properties were characterized by X-ray diffraction (XRD) and transmittance measurements. The films grown have a polycrystalline wurtzite structure and high transmission in the UV-Vis (300-900) nm. The optical energy gap of ZnO:Mg thin films could be controlled between (3.2eV and 3.9eV). The refractive index of ZnO:Mg thin films decreases with Mg doping. The extinction coefficient and the complex dielectric constant were also investigate.

Optical properties of chromium oxide (Cr2O3) thin films which were prepared by pulse laser deposition method, onto glass substrates. Different laser energy (500-900) mJ were used to obtain Cr2O3 thin films with thickness ranging from 177.3 to 372.4 nm were measured using Tolansky method. Then films were annealed at temperature equal to 300 °C. Absorption spectra were used to determine the absorption coefficient of the films, and the effects of the annealing temperature on the absorption coefficient were investigated. The absorption edge shifted to red range of wavelength, and the optical constants of Cr2O3 films increases as the annealing temperature increased to 300 °C. X-ray diffraction (XRD) study reveals that Cr2O3 thin films are a

In this paper will be applied to a probability model of inventories periods of multiple stores of raw materials used in the cement industry, cement factory in Samawah and basic materials are limestone, soil normal, iron soil, fuel oil and gypsum. It was built of this model after the test and determine the distribution of demand during the supply period (waiting period) for each subject and independently of the rest of the material as it is not affected by any of the materials above interrelated in the process of supply, this test has been using the Statistical Package of (SPSS) and then was determining the amount of request optimum seeking in each batch and each substance known volume of economic optimization of

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa