• Journal of Multimedia Information System
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• v.7 no.1
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• pp.1-10
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• 2020

The image analysis is an important and predominant task for classifying the different parts of the image. The analysis of complex image analysis like histopathological define a crucial factor in oncology due to its ability to help pathologists for interpretation of images and therefore various feature extraction techniques have been evolved from time to time for such analysis. Although deep reinforcement learning is a new and emerging technique but very less effort has been made to compare the deep learning and deep reinforcement learning for image analysis. The paper highlights how both techniques differ in feature extraction from complex images and discusses the potential pros and cons. The use of Convolution Neural Network (CNN) in image segmentation, detection and diagnosis of tumour, feature extraction is important but there are several challenges that need to be overcome before Deep Learning can be applied to digital pathology. The one being is the availability of sufficient training examples for medical image datasets, feature extraction from whole area of the image, ground truth localized annotations, adversarial effects of input representations and extremely large size of the digital pathological slides (in gigabytes).Even though formulating Histopathological Image Analysis (HIA) as Multi Instance Learning (MIL) problem is a remarkable step where histopathological image is divided into high resolution patches to make predictions for the patch and then combining them for overall slide predictions but it suffers from loss of contextual and spatial information. In such cases the deep reinforcement learning techniques can be used to learn feature from the limited data without losing contextual and spatial information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.327-335
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• 2001

This paper present to how to make VGIS(Virtual Geographic Information System) using GIS and digital map. Because the development of the GIS has been 2-dimension in the last few years, viewpoint of the high-resolution image estimate was difficult. The geo-spatial information system has lots of errors in the policy decision and the principal decision making because it was displayed as 2 dimension map that the digital map and topographical map, geological map. agronomical map, cadastral map and underground facility map are expressed as a symbol practically in spite that it is spatial topography data. It is utilized as effective administration analyzing, all kinds of discussion, transportation and environmental effect evaluation, various kinds of building discussion and policy decision thorough researching the present condition of region as 3 dimension map using digital map and GIS when drafting and deciding all kinds of urban plaining so it is considered that errors of policy decision will be minimized.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.35-45
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• 2010

The objective of this study is to verify the positional accuracy by performing the orthometric corrections on the high resolution satellite images and to analyze the band correlation between the high resolution images corrected with orthometric correction. The objectives also included an analysis on the correlation of NDVI. For the orthometric correction of images from KOMPSAT2 and IKONOS, systematic errors were removed in use of RPC data, and non-planar distortions were corrected with GPS surveying data. Also, by preempting the image points at the same positions within ortho images, a comparison was performed on positional accuracies between image points of each image and GPS surveying points. The comparison was also made on the positional accuracies of image points. between the images. For correlation of band and correlation of NDVI, the descriptive statistics of DN values were acquired for respective bands by adding the Quickbird images and Aerial Photographs undergone through orthometric correction at the time of purchase. As result, from a comparison on positional accuracies of Orthoimages from KOMPSAT2 and Ortho Images of IKONOS was made. From the comparison the distance between the image points within each image and GPS surveying points was identified as 3.41m for KOMPSAT2 and as 1.45m for IKONOS, presenting a difference of 1.96m. Whereas, RMSE between image points was identified as 1.88m. The level of correlation was measured by using Quickbird, KOMPSAT2, IKONOS and Aerial Photographs between inter-image bands and NDVI, showing that there were high levels of correlation between Quickbird and IKONOS identified from all bands as well as from NDVI, except a high level of correlation that was identified between the Aerial Photographs and KOMPSAT2 from Band 2. Low levels of correlation were also identified between Quickbird and Aerial Photographs from Band 1. and between KOMPSAT2 and IKONOS from Band 2 and Band 4, whereas, KOMPSAT2 showed low correlations with Aerial Photographs from Band 3. For NDVI, KOMPSAT2 showed low level of correlations with both of QuickBird and IKONOS.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.219-233
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• 2013

In this study, spatio-temporal variations of Land Surface Emissivity (LSE) of the three LSE data sets in the Asian-Oceanian regions were addressed. The MODerate Resolution Imaging Spectroradiometer (MODIS) LSE, Cooperative Institute for Meteorological Satellite Studies (CIMSS) LSE, and Kongju National Univ. (KNU) LSE data sets were used. The three data sets showed very similar emissivity in the Tibetan Plateau, desert in the Middle East and Australia, and low latitude regions irrespective of season. The emissivity of $12{\mu}m$ was systematically greater than that of $11{\mu}m$, in particular, in the Tibetan Plateau, desert over Middle East and Australia. In general, they showed a weak seasonal variation in the low latitude regions although the emissivity was different among them. However, the three data sets showed quite different spatial and temporal variations in the other regions of Asian-Oceanian regions. The KNU LSE showed a systematic seasonal variation with a high emissivity during summer and low emissivity during winter but the other two LSE data sets showed irregular seasonal variations without regard to the regions. And the annual mean correlations of $11{\mu}m$ and $12{\mu}m$ between KNU LSE and MODIS LSE (KNU LSE and CIMSS LSE; MODIS LSE and CIMSS LSE) were 0.423 and 0.399 (0.330, 0.101; 0.541, 0.154), respectively. The relatively low correlations and strong inter-month variations, in particular, in $12{\mu}m$, indicated that consistency in spatial variation was very low. The comparison results showed that caution should be given before operational use of the LSE data sets in these regions.

• Korean Journal of Digital Imaging in Medicine
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• v.17 no.1
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• pp.13-18
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• 2015

Purpose : Skip the repetitive HRCT axial scan in order to reduce the exposure of patients during chest HRCT scan, Helical Scan Data into a reconstructed image, and exposure of the patient change and visually evaluate the usefulness of the HRCT images. Materials and method : Patients were enrolled in the survey are 50 people who underwent chest CT scans of patients who presented to the hospital from January 2015 to March 2015. 50 people surveyed 22 people men and 28 people women people showed an average distribution of 30 to 80 years age was 48 years. 50 patients to Somatom Sensation 64 ch (Siemens) model with 120 kVp tube voltage to a reference mAs tube current to mAs (Care dose, Siemens) as a whole, including the lungs and the chest CT scan was performed. Scan upon each patient CARE dose 4D (Automatic exposure control, Siemens Medical Solution Erlangen, Germany) was to maintain the proper radiation dose scan every cross-section through a device that automatically adjusts the tube current of. CT scan is the rotation time of the Tube slice collimation, slice width 0.6 mm, pitch factor was made under the terms of 1.4. CT scan obtained after the raw data (raw data) to the upper surface of the axial images and coronal images for each slice thickness 1 mm, 5 mm intervals in the high spatial frequency calculation method (hight spatial resolution algorithm, B60 sharp) was the use of the lung window center -500 HU, windows were reconstructed into images in the interval -1000 HU to see. Result : 1. Measure the total value of DLP 50 patients who proceed to chest CT group A (Helical Scan after scan performed with HRCT) and group B (Helical Scan after the HR image reconstruction to the original data) compared with the group divided, analysis As a result of the age, but show little difference for each age group it had a decreased average dose of about 9%. 2. A Radiation read the results of the two Radiologist and a doctor upper lobe and middle lobe of the lung takes effect the visual evaluation is not a big difference between the two images both, depending on the age of the patient, especially if the blood vessels of the lower lobe (A: 3.4, B: 4.6) and bronchi(A: 3.8, B4.7) image shake caused by breathing in anxiety (blurring lead) to the original data (raw data) showed that the reconstructed image is been more useful in diagnostic terms. Conclusion : Scan was confirmed a continuous, rapid motion video to get Helical scan is much lower lobe lung reduction in visual blurring, Helical scan data to not repeat the examination by obtaining HRCT images reorganization reduced the exposure of the patient.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• Economic and Environmental Geology
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• v.36 no.6
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• pp.501-510
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• 2003

Several geophysical surveys(electrical resistivity, electromagnetic, seismic refraction, CPR) were conducted to primarily investigate the gallery and the geomembrane at an abandoned mine(Imcheon mine). The subsurface structure mapped from seismic refraction survey mainly consists of three velocity layers(>1000 m/s, 1000∼2000 m/s,＜2000 m/s). Top of the bedrock, whose velocities exceed 2000 m/s, appears to be at depth of 7.5∼10m. Higher resistivities (of ten thousands-hundred of thousands ohm-m) are interpreted to be associated with a open(cavities) gallery. The events at depth of approximately 0.5∼0.7m in GPR sections are probably caused by high-density-poly-ethylene geomembrane. Taking into consideration of the differences in the spatial resolution between georadar and electrical surveys, the events of geomembrane correspond to the top of the high resistivities at depth of about 2m. The segments, characterized with the higher conductivities in the electromagnetic data and the lower resistivities in the electrical resistivity data, are probably associated with surface water or tear zone of geomembrane.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.1-9
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• 2007

Digital Multimedia Broadcasting is the next generation broadcasting service which enables various digital multimedia contents, i.e., audio and video, and data access for mobile users. However, due to the bandwidth limitation, the spatial resolution is limited to CIF(Common Interleaved Frame). The Advanced Terrestrial DMB (AT-DMB) secures additional bandwidth by adopting hierarchical modulation transmission technology and provides high data rate and quality for mobile multimedia broadcasting services with scalable video coding(SVC). This paper proposes scalable video coding technology for AT-DMB which enables high quality mobile multimedia broadcasting services that exceeds current DMB service's quality and contents capability.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.4
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• pp.17-24
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• 2015

This study utilized high quality three-dimensional geospatial information produced by high-resolution Digital Aerial Photograph and Airborne LiDAR data in order to analyse landslides and debris flows induced by the heavy rainfall in Chuncheon area. Also, this study analysed correlation between the established landslide hazard map and the landslide factor effect and reviewed the analysis result of debris flows on the area where landslides with debris flows occurred frequently. Finally;the study proposed ways to renew the established landslide hazard map effectively and utilize the high quality three-dimensional Geospatial information on the landslide risk area.

• Geophysics and Geophysical Exploration
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• v.17 no.4
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• pp.209-215
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• 2014

In order to develop a new mineral exploration technique, a study was carried out about the potential mapping of Moisan area using SIP (Spectral Induced Polarization) data. The SIP inversion results were classified according to the geological regions, and the distribution characteristics of resistivity and phase values of SIP data were analyzed at the ore region. Based on the characteristics of SIP of ore bodies, we performed 3D potential mapping of Moisan area. The analyzed potential map was verified using that the locations and patterns of high potential regions of the results are well matched with those of the known ore bodies. If we get the higher spatial resolution SIP data, the potential mapping technique using SIP data can be effectively applied to the estimation of mining deposit.