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Öğe The Effect of SAR Speckle Removal in SAR-Optical Image Fusion(Institute of Electrical and Electronics Engineers Inc., 2022) Gencay, S.; Ozcan, C.Due to the imaging mechanism of Synthetic Aperture Radar (SAR) and the noise in the images, visual identification of objects in the scene is not as easy as in optical images. SAR images have limited color information and cannot reflect the spectral information of objects. Optical images, on the other hand, have rich spectral information. SAR-Optical image fusion is an important area of study so that SAR data can be easily evaluated by anyone, but it is difficult to find a matching SAR and optical image of the same scene. In order to overcome this difficulty, Sentinel-1 and Sentinel-2 datasets have been published and image fusion studies have been carried out with various methods. However, it has been observed that the effect of SAR noise removal before merging on image fusion methods has not been investigated. In the studies conducted to investigate this effect, five different fusion algorithms used in the literature were tested with twenty different image groups using different noise reduction ratios. The success of the fusion results obtained was compared with five different metrics that are widely used in the literature. The images and metric results obtained as a result of the tests showed that the removal of speckle noise in the SAR data has a positive effect on the fusion results. © 2022 IEEE.Öğe EXTRACTION OF GREENHOUSE AREAS WITH IMAGE PROCESSING METHODS IN KARABUK PROVINCE(Copernicus Gesellschaft Mbh, 2017) Yildirima, M. Z.; Ozcan, C.Greenhouses provide the environmental conditions to be controlled and regulated as desired while allowing agricultural products to be produced without being affected by external environmental conditions. High quality and a wide variety of agricultural products can be produced throughout the year. In addition, mapping and detection of these areas has great importance in terms of factors such as yield analysis, natural resource management and environmental impact. Various remote sensing techniques are currently available for extraction of greenhouse areas. These techniques are based on the automatic detection and interpretation of objects on remotely sensed images. In this study, greenhouse areas were determined from optical images obtained from Landsat. The study was carried out in the greenhouse areas in Karabuk province. The obtained results are presented with figures and tables.Öğe Fast feature preserving despeckling(IEEE Computer Society, 2014) Ozcan, C.; Sen, B.; Nar, F.Synthetic Aperture Radar (SAR) images contain high amount of speckle noise which causes edge detection, shape analysis, classification, segmentation, change detection and target recognition tasks become more difficult. To overcome such difficulties, smoothing of homogenous regions while preserving point scatterers and edges during speckle reduction is quite important. Besides, due to huge size of SAR images in remote sensing applications efficiency of computational load and memory consumption must be further improved. In this paper, a parallel computational approach is proposed for the Feature Preserving Despeckling (FPD) method which is chosen due to its success in speckle reduction. Speckle reduction performance, execution time and memory consumption of the proposed Fast FPD (FFPD) method is shown using spot mode SAR images. © 2014 IEEE.Öğe Fast text classification with Naive Bayes method on Apache Spark(Institute of Electrical and Electronics Engineers Inc., 2017) Ogul, I.U.; Ozcan, C.; Hakdagli, O.The increase in the number of devices and users online with the transition of Internet of Things (IoT), increases the amount of large data exponentially. Classification of ascending data, deletion of irrelevant data, and meaning extraction have reached vital importance in today's standards. Analysis can be done in various variations such as Classification of text on text data, analysis of spam, personality analysis. In this study, fast text classification was performed with machine learning on Apache Spark using the Naive Bayes method. Spark architecture uses a distributed in-memory data collection instead of a distributed data structure presented in Hadoop architecture to provide fast storage and analysis of data. Analyzes were made on the interpretation data of the Reddit which is open source social news site by using the Naive Bayes method. The results are presented in tables and graphs. © 2017 IEEE.Öğe A Review of 3D Indoor Positioning and Navigation in Geographic Information Systems(Springer Science and Business Media Deutschland GmbH, 2024) Kazangirler, B.Y.; Karas, I.R.; Ozcan, C.Geographic information system (GIS) has become widespread with the management of geographically-based information, constituting a large part of the new data obtained and produced today in electronic platform. Three-dimensional (3D) models provide an overview of the more rapid establishment of new ideas that a two-dimensional (2D) visualization cannot present. Thus, 3D GIS demands data to be comprehensive and continious. 3D indoor positioning and 3D navigation are technologies that provide the ability to position and navigate indoors using these systems. The 3D navigation system is a field that can show covering objects in 3D along the route to the goal when precision is involved. In this study, navigation and indoor positioning studies in 3D GIS applications are mentioned, and particularly cutoff edge studies are included. It contains research on the use and benefits of 3D indoor modeling and navigation techniques. The literature examined for the study were evaluated, and it was concluded that 3D indoor positioning and navigation operations were generally performed with algorithms such as map-matching, location-based service, or ML/DL models. We comprehensively review positioning and navigation techniques in the 3D GIS field by combining existing studies, findings, and different approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Öğe Sparsity-driven despeckling method with low memory usage(Institute of Electrical and Electronics Engineers Inc., 2016) Ozcan, C.; Sen, B.; Nar, F.Speckle noise which is inherent to Synthetic Aperture Radar (SAR) imaging makes it difficult to detect targets and recognize spatial patterns on earth. Thus, despeckling is critical and used as a preprocessing step for smoothing homogeneous regions while preserving features such as edges and point scatterers. In this study, a low-memory version of the previously proposed sparsity-driven despeckling (SDD) method is proposed. All steps of the method are parallelized using OpenMP on CPU and CUDA on GPU. Execution time and despeckling performance are shown using real-world SAR images. © 2016 IEEE.Öğe Thermal conductivity of oak impregnated with some chemicals and finished(2010) Sahin, Kol, H.; Uysal, B.; Kurt, S.; Ozcan, C.The objective of this research was to investigate the effects of some impregnation materials and varnishes on the thermal conductivity of oak wood. Ammonium sulfate, borax, boric acid, zinc chloride, diammonium phosphate, and sodium silicate as impregnation chemicals and polyurethane, cellulosic, synthetic, coloured varnishes and cellulosic, synthetic, industrial paints as finishes were used. The wood materials were impregnated by using the vacuum-pressure method. The thermal conductivity test was performed based on the ASTM C 1113-99 hot-wire method. Results showed that the impregnation chemicals increased the thermal conductivity. The highest values were obtained with boric acid and sodium silicate. In addition, the thermal conductivity of painted oak was higher than that of varnished oak. The lowest thermal conductivity of 0.1465 Kcal/mh°C was obtained with the oak control. The highest thermal conductivity of 0.1756 Kcal/mh°C was obtained when oak was painted with industrial paint and impregnated with boric acid.Öğe Total variation based 3D skull segmentation(Institute of Electrical and Electronics Engineers Inc., 2016) Atasoy, F.; Sen, B.; Nar, F.; Ozcan, C.; Bozkurt, I.Segmentation is widely used for determining tumor and other lesions and classifying tissues for various analysis purposes in medical images. However, being an ill-posed problem, there is no single segmentation method which can perform successfully for all kind of data. In this study, a novel total variation (TV) based skull segmentation method is proposed. Skull segmentation performance of the proposed method is shown using computed tomography (CT) images. © 2016 IEEE.
