• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.483-489
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• 2019

True color images display colors similar to natural colors. This has the advantage that it is possible to monitor rapidly the complex earth atmosphere phenomenon and the change of the surface type. Currently, various organizations are producing true color images. In Korea, it is necessary to produce true color images by replacing generations with next generation weather satellites. Therefore, in this study, visual enhancement for true color image production was performed using Top of Atmosphere (TOA) data of Advanced Himawari Imager (AHI) sensor mounted on Himawari-8 satellite. In order to improve the visualization, we performed two methods of Nonlinear enhancement and Histogram equalization. As a result, Histogram equalization showed a strong bluish image in the region over $70^{\circ}$ Solar Zenith Angle (SZA) compared to the Nonlinear enhancement and nonlinear enhancement technique showed a reddish vegetation area.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.101-125
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• 2022

Recently, with the development of computing technology and the improvement of the cloud environment, deep learning technology has developed, and attempts to apply deep learning to various fields are increasing. A typical example is anomaly detection, which is a technique for identifying values or patterns that deviate from normal data. Among the representative types of anomaly detection, it is very difficult to detect a contextual anomaly that requires understanding of the overall situation. In general, detection of anomalies in image data is performed using a pre-trained model trained on large data. However, since this pre-trained model was created by focusing on object classification of images, there is a limit to be applied to anomaly detection that needs to understand complex situations created by various objects. Therefore, in this study, we newly propose a two-step pre-trained model for detecting abnormal situation. Our methodology performs additional learning from image captioning to understand not only mere objects but also the complicated situation created by them. Specifically, the proposed methodology transfers knowledge of the pre-trained model that has learned object classification with ImageNet data to the image captioning model, and uses the caption that describes the situation represented by the image. Afterwards, the weight obtained by learning the situational characteristics through images and captions is extracted and fine-tuning is performed to generate an anomaly detection model. To evaluate the performance of the proposed methodology, an anomaly detection experiment was performed on 400 situational images and the experimental results showed that the proposed methodology was superior in terms of anomaly detection accuracy and F1-score compared to the existing traditional pre-trained model.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.378-390
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• 2022

With the recent development of deep composite multiplication neural network learning, deep learning techniques applied to single-image super-resolution have shown good results, and the strong expression ability of deep networks has enabled complex nonlinear mapping between low-resolution and high-resolution images. However, there are limitations in applying it to real-time or low-power devices with increasing parameters and computational amounts due to excessive use of composite multiplication neural networks. This paper uses blocks that extract hierarchical characteristics little by little using information distillation and suggests the Recursive Distillation Super Resolution Network (RDSRN), a lightweight network that improves performance by making more accurate high frequency components through high frequency residual purification blocks. It was confirmed that the proposed network restores images of similar quality compared to RDN, restores images 3.5 times faster with about 32 times fewer parameters and about 10 times less computation, and produces 0.16 dB better performance with about 2.2 times less parameters and 1.8 times faster processing time than the existing lightweight network CARN.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.

• Restorative Dentistry and Endodontics
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• v.24 no.1
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• pp.100-115
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• 1999

The purpose of this study was to investigate the distribution of calcitonin gene-related peptide containing nerve fibers in rat pulp after dentinl injury by means of immunohistochemistry and confocal laser scanning microscope. The Spague-Dawley rats weighing about 250-300gm were used. The animals were devided into normal control and experimental groups. Experimental animals were sacrified 1, 2, 4, 7, 10, 21days after dentinal injury (dentin cutting, and then acid etching with 35% phosphoric acid) on the maxillary molar teeth. The maxillary teeth and alveolar bone were removed and immersed in the 4% paraformaldehyde in 0.1M phosphate buffer (pH 7.4), then were decalcified with 15% formic acid for 10 days. Serial frozen $50{\mu}m$ thick sections were cut on a cryostat. The rabbit CGRP antibody was used as a primary antibody with a dilution of 1:2000 in 0.01M PB. The sections were incubated for 48 hours at $4^{\circ}C$, and placed into biotinylated antirabbit Ig G as a secondary anti body with dilution of 1:200 in 0.01M PB and incubated in ABC(avidin-biotin complex). The peroxidase reaction was visualized by incubating the sections in 0.05% 3,3 diaminobenzidine tetrahydrochloride containing 0.02% $H_2O_2$. For the confocal laser scanning microscopic examination, Primary antibody reaction was same as immunoperoxidase stainning, but fluorescein isothiocyanate(FITC)-conjugate antirabbit IgG as a secondary antibody was used. The confocal laser scanning microscope was used for the examination. A series of images of optical sections was collected with a 20x objective at $3{\mu}m$ intervals throughout the depth of specimen. FITC fluerescence was registrated through a 488nm and 568nm excitation filter, and images were saved on optical disk. The stereoscopic images and three dimentionnal images were reconstructed by computer software, and then were analyzed. The results were as follows : 1. In normal control group, CGRP containing nerve fibers were coursed through the root with very little branching, and then formed a dense network of terminals in coronal pulp. 2. A slight increase in CGRP containing nerve fibers at 1 and 2day postinjury was noted subjacent to the injury site. In the 4day group, there were an extensive increase in the number of reactive fibers, followed by a partial return toward normal levels at 7~10 day postinjury, and return by 21days. 3. The sprouting of the CGRP containing nerve fibers was evident within 2day after dentinal injury, and by 4days there was a maximal increased, but was decreased at 7days and returned to normal 10~21 day postinjury. 4. In confocal laser scanning microscopic exammination, the distinct distribution pattern and sprouting reaction of CGRP containing nerve fibers were observed in stereoscopic images and three dimentional images. These results suggest that CGRP containing nerve fiber can be important role in the response to dental injury and pain regulation.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.241-252
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• 2004

Purpose: Population based structural and functional maps of the brain provide effective tools for the analysis and interpretation of complex and individually variable brain data. Brain MRI and PET standard templates and statistical probabilistic maps based on image data of Korean normal volunteers have been developed and probabilistic maps based on cytoarchitectonic data have been introduced. A quantification method using these data was developed for the objective assessment of regional intensity in the brain images. Materials and Methods: Age, gender and ethnic specific anatomical and functional brain templates based on MR and PET images of Korean normal volunteers were developed. Korean structural probabilistic maps for 89 brain regions and cytoarchitectonic probabilistic maps for 13 Brodmann areas were transformed onto the standard templates. Brain FDG PET and SPGR MR images of normal volunteers were spatially normalized onto the template of each modality and gender. Regional uptake of radiotracers in PET and gray matter concentration in MR images were then quantified by averaging (or summing) regional intensities weighted using the probabilistic maps of brain regions. Regionally specific effects of aging on glucose metabolism in cingulate cortex were also examined. Results: Quantification program could generate quantification results for single spatially normalized images per 20 seconds. Glucose metabolism change in cingulate gyrus was regionally specific: ratios of glucose metabolism in the rostral anterior cingulate vs. posterior cingulate and the caudal anterior cingulate vs. posterior cingulate were significantly decreased as the age increased. 'Rostral anterior'/'posterior' was decreased by 3.1% per decade of age ($P<10^{-11}$, r=0.81) and 'caudal anterior'/'posterior' was decreased by 1.7% ($P<10^{-8}$, r=0.72). Conclusion: Ethnic specific standard templates and probabilistic maps and quantification program developed in this study will be useful for the analysis of brain image of Korean people since the difference in shape of the hemispheres and the sulcal pattern of brain relative to age, gender, races, and diseases cannot be fully overcome by the nonlinear spatial normalization techniques.

• Economic and Environmental Geology
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• v.49 no.5
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• pp.381-388
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• 2016

The purpose of this study is to integrate and visualize using mapping techniques based on precise seabed geomorphology, seafloor backscattering images and high-resolution underwater images of the nearshore area around the Dokdo, in the East Sea. We have been obtained the precise topography map using multibeam echosounder system around the nearshore area(~50 m) of the southern part of the Seodo. Side scan sonar survey for analysis seafloor backscattering images was carried out in the same area of topography data. High-resolution underwater images(zone(a), zone(b), zone(c)) were taken in significant habitat scope of the nearshore area of the southern part of the Seodo. Using the results of bathymetry, seafloor backscattering images, high-resolution underwater images, we performed an integrated visualization about the nearshore area of the Dokdo. The integrated visualizing techniques are possible to make the seabed characteristic mapping results of the nearshore area of the Dokdo. The integrated visualization results present more complex and reliable information than separate geological products for seabed environmental mapping study and it is useful to understand the relation between seafloor characteristics and topographic environments of the study area. The integrated visualizing techniques and mapping analysis need to study sustainably and periodically, for effective monitoring of the nearshore ecosystem of the Dokdo.

• Journal of the Korean Society of Radiology
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• v.17 no.4
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• pp.607-614
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• 2023

Clear overlapping of the bilateral epicondyle and proper separation of the elbow joint are crucial for obtaining accurate lateral general radiographs of the elbow. However, due to the complex anatomical structure of the elbow, achieving optimal positioning is challenging, leading to the need for repeated x-ray examinations. Therefore, the purpose of this study was to investigate the angle of the forearm in patients where accurate lateral images of the elbow joint can't be obtained after vertical incidence using a styrofoam device during elbow joint lateral x-ray imaging. Twenty patients were enrolled in our study following the established protocol. First, a vertical x-ray at an angle of 0° between the forearm and the table was taken (control group). Here, if the lateral image of the elbow joint was deemed inadequate, the forearm angle was adjusted using custom-made styrofoam supports with 5° and 10° inclinations (experimental groups). For the evaluation method, two assessors utilized a 5-point Likert scale to assess the images. The reliability of the assessments was analyzed using Cronbach's alpha coefficient. As a result, patients with inadequate overlap of the bilateral epicondyle and separation of the elbow joint in the initial examination (control group) were able to obtain the best images when setting a 10° angle between the forearm and the table. The subjective evaluation was 1.6 ± 0.8 points at 0°, 2.7 ± 0.8 points at 5°, and 4.4 ± 1.3 points at 10°, respectively. The reliability analysis for the angles of 0°, 5°, and 10° yielded Cronbach's alpha values of 0.867, 0.697, and 0.922, respectively. In conclusion, when it is not possible to obtain accurate images using the conventional position and X-ray beam direction, it is considered that by initially acquiring images with an angle of 10° between the forearm and the table, and gradually decreasing the angle while obtaining images, it would be possible to achieve the optimal image while reducing the number of repeat examinations.