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Öğe Overview of computer gaphics and algorithms(IEEE, 2015-05) Çalışkan, Abidin; Çevik, UlusComputer Graphics (CG) is the art of rendering, and visualizing images on the computer screens. In three-dimensional (3D) CG, a scene is first modeled geometrically, typically using triangles, and the computer is then used to calculate what the scene will look like from a specific view point at a particular instant. In CG, one of the major goals is to create photo-realistic images in real time. In recent years, Volume Visualization (VV) has attracted the attention of many researchers. VV techniques have been used to analyze and render 3D datasets, obtained from a variety of sources including medical scanners, and results of simulation of physical and synthetic phenomena, on the computer screen. Volume Graphics (VG) has proven itself as an independent graphics technology. A common purpose of VG is to achieve photo realistic rendering. To achieve this, reflections, shadows, refraction and perspective projections are all necessary elements since they occur naturally in the natural environment.Öğe An efficient noisy pixels detection model for CT images using extreme learning machines(Sveuciliste Josipa Jurja Strossmayera u Osijeku, 2018-06) Çalışkan, Abidin; Çevik, UlusIn this study, a new and rapid hidden resource decomposition method has been proposed to determine noisy pixels by adopting the extreme learning machines (ELM) method. The goal of this method is not only to determine noisy pixels, but also to protect critical structural information that can be used for disease diagnosis. In order to facilitate the diagnosis and also the treatment of patients in medicine, two-dimensional (2-D) images were calculated tomography (CT) which is obtained using medical imaging techniques. Utilizing a large number of CT images, promising results have been obtained from these experiments. The proposed method has shown a significant improvement on mean squared error and peak signal-to-noise ratio. The experimental results indicate that the proposed method is statistically efficient, and it has a good performance with a high learning speed. In the experiments, the results demonstrated that remarkable successive rates were obtained through the ELM method.
